
Every hour you wait is a signal you miss.

Stop Guessing, Start Trading: The Token Metrics API Advantage
Big news: We’re cranking up the heat on AI-driven crypto analytics with the launch of the Token Metrics API and our official SDK (Software Development Kit). This isn’t just an upgrade – it's a quantum leap, giving traders, hedge funds, developers, and institutions direct access to cutting-edge market intelligence, trading signals, and predictive analytics.
Crypto markets move fast, and having real-time, AI-powered insights can be the difference between catching the next big trend or getting left behind. Until now, traders and quants have been wrestling with scattered data, delayed reporting, and a lack of truly predictive analytics. Not anymore.
The Token Metrics API delivers 32+ high-performance endpoints packed with powerful AI-driven insights right into your lap, including:
- Trading Signals: AI-driven buy/sell recommendations based on real-time market conditions.
- Investor & Trader Grades: Our proprietary risk-adjusted scoring for assessing crypto assets.
- Price Predictions: Machine learning-powered forecasts for multiple time frames.
- Sentiment Analysis: Aggregated insights from social media, news, and market data.
- Market Indicators: Advanced metrics, including correlation analysis, volatility trends, and macro-level market insights.
Getting started with the Token Metrics API is simple:
- Sign up at www.tokenmetrics.com/api.
- Generate an API key and explore sample requests.
- Choose a tier–start with 50 free API calls/month, or stake TMAI tokens for premium access.
- Optionally–download the SDK, install it for your preferred programming language, and follow the provided setup guide.
At Token Metrics, we believe data should be decentralized, predictive, and actionable.
The Token Metrics API & SDK bring next-gen AI-powered crypto intelligence to anyone looking to trade smarter, build better, and stay ahead of the curve. With our official SDK, developers can plug these insights into their own trading bots, dashboards, and research tools – no need to reinvent the wheel.
Mastering the ChatGPT API: Practical Developer Guide
ChatGPT API has become a foundational tool for building conversational agents, content generation pipelines, and AI-powered features across web and mobile apps. This guide walks through how the API works, common integration patterns, cost and performance considerations, prompt engineering strategies, and security and compliance checkpoints — all framed to help developers design reliable, production-ready systems.
Overview: What the ChatGPT API Provides
The ChatGPT API exposes a conversational, instruction-following model through RESTful endpoints. It accepts structured inputs (messages, system instructions, temperature, max tokens) and returns generated messages and usage metrics. Key capabilities include multi-turn context handling, role-based prompts (system, user, assistant), and streaming responses for lower perceived latency.
When evaluating the API for a project, consider three high-level dimensions: functional fit (can it produce the outputs you need?), operational constraints (latency, throughput, rate limits), and cost model (token usage and pricing). Structuring experiments around these dimensions produces clearer decisions than ad-hoc prototyping.
How the ChatGPT API Works: Architecture & Tokens
At a technical level, the API exchanges conversational messages composed of roles and content. The model's input size is measured in tokens, not characters; both prompts and generated outputs consume tokens. Developers must account for:
- Input tokens: system+user messages sent with the request.
- Output tokens: model-generated content returned in the response.
- Context window: maximum tokens the model accepts per request, limiting historical context you can preserve.
Token-awareness is essential for cost control and designing concise prompts. Tools exist to estimate token counts for given strings; include these estimates in batching and truncation logic to prevent failed requests due to exceeding the context window.
Integration Patterns and Use Cases
Common patterns for integrating the ChatGPT API map to different functional requirements:
- Frontend chat widget: Short, low-latency requests per user interaction with streaming enabled for better UX.
- Server-side orchestration: Useful for multi-step workflows, retrieving and combining external data before calling the model.
- Batch generation pipelines: For large-scale content generation, precompute outputs asynchronously and store results for retrieval.
- Hybrid retrieval-augmented generation (RAG): Combine a knowledge store or vector DB with retrieval calls to ground responses in up-to-date data.
Select a pattern based on latency tolerance, concurrency requirements, and the need to control outputs with additional logic or verifiable sources.
Cost, Rate Limits, and Performance Considerations
Pricing for ChatGPT-style APIs typically ties to token usage and model selection. For production systems, optimize costs and performance by:
- Choosing the right model: Use smaller models for routine tasks where quality/latency tradeoffs are acceptable.
- Prompt engineering: Make prompts concise and directive to reduce input tokens and avoid unnecessary generation.
- Caching and deduplication: Cache common queries and reuse cached outputs when applicable to avoid repeated cost.
- Throttling: Implement exponential backoff and request queuing to respect rate limits and avoid cascading failures.
Measure end-to-end latency including network, model inference, and application processing. Use streaming when user-perceived latency matters; otherwise, batch requests for throughput efficiency.
Best Practices: Prompt Design, Testing, and Monitoring
Robust ChatGPT API usage blends engineering discipline with iterative evaluation:
- Prompt templates: Maintain reusable templates with placeholders to enforce consistent style and constraints.
- Automated tests: Create unit and integration tests that validate output shape, safety checks, and critical content invariants.
- Safety filters and moderation: Run model outputs through moderation or rule-based filters to detect unwanted content.
- Instrumentation: Log request/response sizes, latencies, token usage, and error rates. Aggregate metrics to detect regressions.
- Fallback strategies: Implement graceful degradation (e.g., canned responses or reduced functionality) when API latency spikes or quota limits are reached.
Adopt iterative prompt tuning: A/B different system instructions, sampling temperatures, and max tokens while measuring relevance, correctness, and safety against representative datasets.
Build Smarter Crypto Apps & AI Agents with Token Metrics
Token Metrics provides real-time prices, trading signals, and on-chain insights all from one powerful API. Grab a Free API Key
FAQ: What is the ChatGPT API and when should I use it?
The ChatGPT API is a conversational model endpoint for generating text based on messages and instructions. Use it when you need flexible, context-aware text generation such as chatbots, summarization, or creative writing assistants.
FAQ: How do tokens impact cost and context?
Tokens measure both input and output size. Longer prompts and longer responses increase token counts, which raises cost and can hit the model's context window limit. Optimize prompts and truncate history when necessary.
FAQ: What are common strategies for handling rate limits?
Implement client-side throttling, request queuing, exponential backoff on 429 responses, and prioritize critical requests. Monitor usage patterns and adjust concurrency to avoid hitting provider limits.
FAQ: How do I design effective prompts?
Start with a clear system instruction to set tone and constraints, use examples for format guidance, keep user prompts concise, and test iteratively. Templates and guardrails reduce variability in outputs.
FAQ: What security and privacy practices should I follow?
Secure API keys (do not embed in client code), encrypt data in transit and at rest, anonymize sensitive user data when possible, and review provider data usage policies. Apply access controls and rotate keys periodically.
FAQ: When should I use streaming responses?
Use streaming to improve perceived responsiveness for chat-like experiences or long outputs. Streaming reduces time-to-first-token and allows progressive rendering in UIs.
Disclaimer
This article is for informational and technical guidance only. It does not constitute legal, compliance, or investment advice. Evaluate provider terms and conduct your own testing before deploying models in production.
Mastering the OpenAI API: Practical Guide
The OpenAI API has become a foundation for building modern AI applications, from chat assistants to semantic search and generative agents. This post breaks down how the API works, core endpoints, implementation patterns, operational considerations, and practical tips to get reliable results while managing cost and risk.
How the OpenAI API Works
The OpenAI API exposes pre-trained and fine-tunable models through RESTful endpoints. At a high level, you send text or binary payloads and receive structured responses — completions, chat messages, embeddings, or file-based fine-tune artifacts. Communication is typically via HTTPS with JSON payloads. Authentication uses API keys scoped to your account, and responses include usage metadata to help with monitoring.
Understanding the data flow is useful: client app → API request (model, prompt, params) → model inference → API response (text, tokens, embeddings). Latency depends on model size, input length, and concurrency. Many production systems put the API behind a middleware layer to handle retries, caching, and prompt templating.
Key Features & Endpoints
The API surface typically includes several core capabilities you should know when planning architecture:
- Chat/Completion: Generate conversational or free-form text. Use system, user, and assistant roles for structured prompts.
- Embeddings: Convert text to dense vectors for semantic search, clustering, and retrieval-augmented generation.
- Fine-tuning: Customize models on domain data to improve alignment with specific tasks.
- Files & Transcriptions: Upload assets for fine-tune datasets or to transcribe audio to text.
- Moderation & Safety Tools: Automated checks can help flag content that violates policy constraints before generation is surfaced.
Choosing the right endpoint depends on the use case: embeddings for search/indexing, chat for conversational interfaces, and fine-tuning for repetitive, domain-specific prompts where consistency matters.
Practical Implementation Tips
Design patterns and practical tweaks reduce friction in real-world systems. Here are tested approaches:
- Prompt engineering and templates: Extract frequently used structures into templates and parameterize variables. Keep system messages concise and deterministic.
- Chunking & retrieval: For long-context tasks, use embeddings + vector search to retrieve relevant snippets and feed only the most salient content into the model.
- Batching & caching: Batch similar requests where possible to reduce API calls. Cache embeddings and immutable outputs to lower cost and latency.
- Retry logic and idempotency: Implement exponential backoff for transient errors and idempotent request IDs for safe retries.
- Testing and evaluation: Use automated tests to validate response quality across edge cases and measure drift over time.
For development workflows, maintain separate API keys and quotas for staging and production, and log both prompts and model responses (with privacy controls) to enable debugging and iterative improvement.
Security, Cost Control, and Rate Limits
Operational concerns are often the difference between a prototype and a resilient product. Key considerations include:
- Authentication: Store keys securely, rotate them regularly, and avoid embedding them in client-side code.
- Rate limits & concurrency: Respect published rate limits. Use client-side queues and server-side throttling to smooth bursts and avoid 429 errors.
- Cost monitoring: Track token usage by endpoint and user to identify high-cost flows. Use sampling and quotas to prevent runaway spend.
- Data handling & privacy: Define retention and redaction rules for prompts and responses. Understand whether user data is used for model improvement and configure opt-out where necessary.
Instrumenting observability — latency, error rates, token counts per request — lets you correlate model choices with operational cost and end-user experience.
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What are common failure modes and how to mitigate them?
Common issues include prompt ambiguity, hallucinations, token truncation, and rate-limit throttling. Mitigation strategies:
- Ambiguity: Add explicit constraints and examples in prompts.
- Hallucination: Use retrieval-augmented generation and cite sources where possible.
- Truncation: Monitor token counts and implement summarization or chunking for long inputs.
- Throttling: Apply client-side backoff and request shaping to prevent bursts.
Run adversarial tests to discover brittle prompts and incorporate guardrails in your application logic.
Scaling and Architecture Patterns
For scale, separate concerns into layers: ingestion, retrieval/indexing, inference orchestration, and post-processing. Use a vector database for embeddings, a message queue for burst handling, and server-side orchestration for prompt composition and retries. Edge caching for static outputs reduces repeated calls for common queries.
Consider hybrid strategies where smaller models run locally for simple tasks and the API is used selectively for high-value or complex inferences to balance cost and latency.
FAQ: How to get started and troubleshoot
What authentication method does the OpenAI API use?
Most implementations use API keys sent in an Authorization header. Keys must be protected server-side. Rotate keys periodically and restrict scopes where supported.
Which models are best for embeddings versus chat?
Embedding-optimized models produce dense vectors for semantic tasks. Chat or completion models prioritize dialogue coherence and instruction-following. Select based on task: search and retrieval use embeddings; conversational agents use chat endpoints.
How can I reduce latency for user-facing apps?
Use caching, smaller models for simple tasks, pre-compute embeddings for common queries, and implement warm-up strategies. Also evaluate regional endpoints and keep payload sizes minimal to reduce round-trip time.
What are best practices for fine-tuning?
Curate high-quality, representative datasets. Keep prompts consistent between fine-tuning and inference. Monitor for overfitting and validate on held-out examples to ensure generalization.
How do I monitor and manage costs effectively?
Track token usage by endpoint and user journey, set per-key quotas, and sample outputs rather than logging everything. Use batching and caching to reduce repeated calls, and enforce strict guards on long or recursive prompts.
Can I use the API for production-critical systems?
Yes, with careful design. Add retries, fallbacks, safety checks, and human-in-the-loop reviews for high-stakes outcomes. Maintain SLAs that reflect model performance variability and instrument monitoring for regressions.
Disclaimer
This article is for educational purposes only. It explains technical concepts, implementation patterns, and operational considerations related to the OpenAI API. It does not provide investment, legal, or regulatory advice. Always review provider documentation and applicable policies before deploying systems.
Inside DeepSeek API: Advanced Search for Crypto Intelligence
DeepSeek API has emerged as a specialized toolkit for developers and researchers who need granular, semantically rich access to crypto-related documents, on-chain data, and developer content. This article breaks down how the DeepSeek API works, common integration patterns, practical research workflows, and how AI-driven platforms can complement its capabilities without making investment recommendations.
What the DeepSeek API Does
The DeepSeek API is designed to index and retrieve contextual information across heterogeneous sources: whitepapers, GitHub repos, forum threads, on-chain events, and more. Unlike keyword-only search, DeepSeek focuses on semantic matching—returning results that align with the intent of a query rather than only literal token matches.
Key capabilities typically include:
- Semantic embeddings for natural language search.
- Document chunking and contextual retrieval for long-form content.
- Metadata filtering (chain, contract address, author, date).
- Streamed or batched query interfaces for different throughput needs.
Typical Architecture & Integration Patterns
Integrating the DeepSeek API into a product follows common design patterns depending on latency and scale requirements:
- Server-side retrieval layer: Your backend calls DeepSeek to fetch semantically ranked documents, then performs post-processing and enrichment before returning results to clients.
- Edge-caching and rate management: Cache popular queries and embeddings to reduce costs and improve responsiveness. Use exponential backoff and quota awareness for production stability.
- AI agent workflows: Use the API to retrieve context windows for LLM prompts—DeepSeek's chunked documents can help keep prompts relevant without exceeding token budgets.
When building integrations, consider privacy, data retention, and whether you need to host a private index versus relying on a hosted DeepSeek endpoint.
Research Workflows & Practical Tips
Researchers using the DeepSeek API can follow a repeatable workflow to ensure comprehensive coverage and defensible results:
- Define intent and query templates: Create structured queries that capture entity names, contract addresses, or conceptual prompts (e.g., “protocol upgrade risks” + contract).
- Layer filters: Use metadata to constrain results to a chain, date range, or document type to reduce noise.
- Iterative narrowing: Start with wide semantic searches, then narrow with follow-up queries using top results as new seeds.
- Evaluate relevance: Score results using both DeepSeek’s ranking and custom heuristics (recency, authoritativeness, on-chain evidence).
- Document provenance: Capture source URLs, timestamps, and checksums for reproducibility.
For reproducible experiments, version your query templates and save query-result sets alongside analysis notes.
Limitations, Costs, and Risk Factors
Understanding the constraints of a semantic retrieval API is essential for reliable outputs:
- Semantic drift: Embeddings and ranking models can favor topical similarity that may miss critical technical differences. Validate with deterministic checks (contract bytecode, event logs).
- Data freshness: Indexing cadence affects the visibility of the newest commits or on-chain events. Verify whether the API supports near-real-time indexing if that matters for your use case.
- Cost profile: High-volume or high-recall retrieval workloads can be expensive. Design sampling and caching strategies to control costs.
- Bias and coverage gaps: Not all sources are equally represented. Cross-check against primary sources where possible.
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Token Metrics provides real-time prices, trading signals, and on-chain insights all from one powerful API. Grab a Free API Key
FAQ: What developers ask most about DeepSeek API
What data sources does DeepSeek index?
DeepSeek typically indexes a mix of developer-centric and community data: GitHub, whitepapers, documentation sites, forums, and on-chain events. Exact coverage depends on the provider's ingestion pipeline and configuration options you choose when provisioning indexes.
How do embeddings improve search relevance?
Embeddings map text into vector space where semantic similarity becomes measurable as geometric closeness. This allows queries to match documents by meaning rather than shared keywords, improving recall for paraphrased or conceptually related content.
Can DeepSeek return structured on-chain data?
While DeepSeek is optimized for textual retrieval, many deployments support linking to structured on-chain records. A common pattern is to return document results with associated on-chain references (contract addresses, event IDs) so downstream systems can fetch transaction-level details from block explorers or node APIs.
How should I evaluate result quality?
Use a combination of automated metrics (precision@k, recall sampling) and human review. For technical subjects, validate excerpts against source code, transaction logs, and authoritative docs to avoid false positives driven by surface-level similarity.
What are best practices for using DeepSeek with LLMs?
Keep retrieved context concise and relevant: prioritize high-salience chunks, include provenance for factual checks, and use retrieval augmentation to ground model outputs. Also, monitor token usage and prefer compressed summaries for long sources.
How does it compare to other crypto APIs?
DeepSeek is focused on semantic retrieval and contextual search, while other crypto APIs may prioritize raw market data, on-chain metrics, or analytics dashboards. Combining DeepSeek-style search with specialized APIs (for price, on-chain metrics, or signals) yields richer tooling for research workflows.
Where can I learn more or get a demo?
Explore provider docs and example use cases. For integrated AI research and ratings, see Token Metrics which demonstrates how semantic retrieval can be paired with model-driven analysis for structured insights.
Disclaimer
This article is for informational and technical education only. It does not constitute investment advice, endorsements, or recommendations. Evaluate tools and data sources critically and consider legal and compliance requirements before deployment.
Recent Posts

Crypto Index Fund: How AI Is Revolutionizing Crypto Index Investment
The Rise of Crypto Index Funds
As the cryptocurrency market matures, investors are increasingly seeking structured and diversified ways to participate without picking individual tokens. Just as index funds transformed traditional finance, crypto index funds are reshaping digital asset investing. These funds allow investors to gain broad exposure to the crypto market through a single investment vehicle, making them a compelling choice for both new and experienced participants.
But in a fast-moving, data-heavy environment like crypto, efficiency is everything. This is where AI-enhanced crypto index investment comes in—offering smarter rebalancing, risk management, and data-driven selection strategies that outperform traditional index methodologies.
What Are Crypto Index Funds?
A crypto index fund is a digital asset investment product that tracks the performance of a group of cryptocurrencies, typically weighted by market capitalization, theme, or other quantitative factors. Similar to traditional index funds in equities (like the S&P 500), a crypto index aggregates tokens into a single, trackable basket, allowing investors to diversify easily.
Key Features of Crypto Index Funds:
- Diversification: Spread risk across multiple crypto assets.
- Passive Investment: No need to actively trade or research individual tokens.
- Low Fees: Typically lower management costs than hedge funds or active trading.
- Rebalancing: Regular updates to maintain target weights and asset mix.
- Transparency: Index compositions and methodologies are usually public.
Popular Crypto Index Themes:
- Top 10 or Top 25 by Market Cap
- DeFi Index: Includes projects like Uniswap, Aave, Compound.
- AI Tokens Index: Focused on artificial intelligence crypto projects.
- NFT Index: Tracks platforms like Blur, Rarible, or OpenSea tokens.
- Meme Coin Index: A speculative basket for high-risk investors.
Why Crypto Index Investment Is Gaining Popularity
Crypto markets are volatile, fast-moving, and often driven by unpredictable narratives. Many investors, especially institutions or those new to the space, are uncomfortable managing a portfolio of dozens of altcoins. That’s where crypto index investment provides a safe entry point.
Benefits of Crypto Index Funds:
- Reduced Volatility: Spreading capital over multiple assets cushions against extreme swings.
- Time-Saving: Investors don’t have to stay glued to charts or news.
- Risk Management: Poor performers get phased out during rebalancing.
- Benchmarking: Investors can measure their returns against established crypto indices.
The Problem with Traditional Crypto Index Funds
Despite their advantages, most crypto index funds still rely on static rule sets:
- Fixed Rebalancing Intervals: Usually monthly or quarterly, which may not align with real-time market shifts.
- Market Cap Bias: Overexposure to large-cap tokens can dilute exposure to high-growth assets.
- No Signal Integration: They ignore on-chain activity, social sentiment, or developer metrics.
In a market as dynamic as crypto, these limitations mean missed opportunities and reduced alpha.
Enter AI: The Future of Efficient Crypto Index Funds
AI is revolutionizing how crypto indices are built, managed, and optimized. By ingesting real-time data from hundreds of sources, AI-powered systems can outperform static, rules-based indices in terms of returns, risk mitigation, and adaptability.
How AI Enhances Crypto Index Investment:
- Dynamic Rebalancing Based on Signals
- Instead of rigid monthly rebalancing, AI uses market signals (e.g., momentum, trend strength, liquidity) to adjust allocations daily or even hourly.
- Example: Exiting meme tokens during a bearish shift, reallocating to AI tokens gaining traction.
- Sentiment Analysis and News Detection
- AI scans Twitter, Reddit, Telegram, and news sites for bullish/bearish sentiment, helping identify trends before they go mainstream.
- This is crucial for niche tokens with limited historical data.
- On-Chain Metrics and Smart Contract Activity
- AI monitors transaction volumes, active wallets, staking ratios, and developer commits to detect growth or decline before prices reflect it.
- Risk-Adjusted Weighting Models
- Rather than simply weighting by market cap, AI uses volatility, Sharpe ratio, and correlation models to dynamically assign weights.
- This reduces overexposure to volatile assets and boosts overall portfolio efficiency.
- Backtesting and Optimization
- AI can simulate thousands of portfolio combinations over historical data to find optimal strategies based on the user’s risk profile.
Real-World Example: AI-Driven Crypto Index Platforms
Some platforms are already pioneering AI-powered crypto indices:
- Token Metrics AI Indices: Combine machine learning with market sentiment to allocate and rebalance crypto portfolios automatically. They feature bullish and bearish signals that guide when to enter or exit an index.
- Bitwise & Galaxy Indices: Though more traditional, they’re beginning to explore data-driven rebalancing and smart beta strategies.
- DeFi Pulse Index (DPI): A static sector index for DeFi, but when enhanced with AI (e.g., incorporating protocol usage data), it could evolve into a dynamic performer.
The Future: Personalized AI Crypto Index Funds
Imagine a world where your crypto portfolio isn’t just passively tracking a fixed list—but actively evolving based on your risk profile, market trends, and even your trading behavior.
AI will enable:
- User-Customized Indices: Choose themes (e.g., AI, RWA, Gaming) and let AI build and manage the ideal mix.
- Automated Exit Strategies: AI detects early warning signals and reallocates your funds to stablecoins.
- Goal-Based Investing: AI manages your crypto portfolio to hit a target (e.g., 15% annualized return or reduce drawdowns under 10%).
Final Thoughts: Best Crypto Index Investing Starts with AI
Crypto index funds offer a powerful solution for investors looking to simplify their entry into the world of digital assets. But in a space defined by speed, volatility, and complexity, static methods are quickly becoming outdated.
By incorporating AI into crypto index investment, the future becomes more adaptive, predictive, and personalized. Whether you're a passive investor or an active trader looking for an edge, AI-powered crypto indices are unlocking a new frontier in digital wealth creation.

Build the Future of Crypto Trading: Integrating Token Metrics with LangChain for Smarter Crypto Decisions
The rise of AI in crypto trading has opened new frontiers, and Token Metrics is leading the charge by enabling developers to build intelligent trading agents using its powerful API. The latest innovation? A seamless integration with LangChain – a popular framework for building context-aware agents using large language models (LLMs). In this blog post, we’ll break down how this integration works, what it enables, and why it represents a game-changing leap in automated crypto analysis.
What is LangChain?
LangChain is an open-source framework that helps developers build applications powered by large language models like Gemini, Claude, and OpenAI. It enables developers to build a wide range of advanced AI solutions, including:
- Conversational agents
- Retrieval-based question answering
- Tool-using AI agents
- Autonomous decision-making bots
By providing a flexible structure, LangChain makes it easy to integrate LLMs with real-world data sources and external tools, empowering your application to both reason and take action.
What is the Token Metrics API?
The Token Metrics API is a rich data layer for crypto investors, analysts, and builders. It provides real-time and historical data across:
- AI-powered Trader and Investor Grades
- Daily/Hourly OHLCV metrics
- Bullish/Bearish AI signals
- Quantitative indicators
- Curated Crypto Indices
With over 80 data points per token and robust filtering, the API makes it easy to identify profitable tokens, spot market trends, and build intelligent trading strategies.
Why Combine LangChain and Token Metrics?
Combining LangChain with Token Metrics lets you build AI-powered crypto agents that deliver market analysis and actionable insights. These agents can:
- Analyze crypto prices, trends, and sentiment using AI-driven methods
- Apply predefined strategies or custom logic for automated decision making
- Generates clear, human-readable insights and trading signals
- Identify and highlight tokens with strong profit potential
This integration equips your crypto applications with intelligent, data-driven capabilities to support smarter trading and research.
Getting Started: Building the Agent
The integration process begins with cloning a GitHub repository (public upon video release), which includes everything needed to run a Token Metrics x LangChain demo agent. After installing the dependencies and opening the codebase in a code editor, you’ll find a fully documented README that walks you through the setup.
Step 1: Install Dependencies
Navigate to the project directory and install the required packages using:

Step 2: Configure Environment Variables
Before spinning up the agent, add your Token Metrics API key and your LLM API key (Openai, gemini, etc..) to the .env file. These credentials authorize the agent to access both Token Metrics and your chosen LLM.

Step 3: Define and Run the Agent
The agent logic is explained directly in the README and starter code sample, making it easy to follow and customize. You’ll find clear instructions and code snippets that guide you through setting up the agent’s capabilities.
The agent supports two main modes:
- Simple Agent: A straightforward agent that answers user questions using Token Metrics tools. It’s ideal for quick queries and basic crypto research tasks.
- Advanced Agent: A more powerful agent capable of reasoning through complex tasks, chaining together multiple tools, and providing deeper analysis. This agent can handle multi-step queries and deliver more comprehensive insights.
Powered by LangChain’s ReAct (Reasoning + Acting) framework, your agent can:
- Access a suite of Token Metrics tools for crypto analysis, including price data, trading signals, grades, and sentiment
- Apply predefined strategies or custom logic for automated decision-making
- Generate clear, human-readable insights and trading signals
- Filter and highlight tokens based on objective, data-driven criteria
With comprehensive documentation and step-by-step guidance in the README, you can quickly build, customize, and deploy your own intelligent crypto research assistant—no separate agent.py file required.
A Real-World Example: Finding Winning Tokens
Here’s how the agent works in practice:
- It queries tokens with a valid Trader Grade
- Filters tokens with Bullish AI signals
- Compares Trading Signal ROI vs Holding ROI
- Filters out tokens that aren’t outperforming with active trading
In the test case, it identifies BANANAS S31 as a top candidate:
- High trader grade
- Bullish signal
- Strong Trading Signal ROI (better than holding)
At the end of its analysis, the bot outputs a summary of:
- Overall market sentiment
- Top token opportunities
- Macro-level recommendations
In this case, while BANANAS S31 stood out, the overall market leaned neutral with a slight long-term bearish bias, a useful snapshot for any trader.
Switching to the Advanced Agent
LangChain’s flexibility allows the same bot to switch into an interactive chatbot by attaching memory to the agent. Users can now type in:
“What are the top 3 tokens to watch today?”
“Is the market bullish or bearish?”
“Give me DeFi tokens with bullish signals.”
The agent can dynamically select and chain together specialized crypto analysis tools in response to your questions. This means the agent doesn’t just answer queries with static information but it actively pulls the latest Token Metrics data, applies AI-driven analytics, and synthesizes insights using multiple sources and methods.
As a result, you will get clear, context-aware responses about market trends, trading signals, token performance, and more. All grounded by the Token Metrics APIs
Key Benefits of This Integration
Here’s why this LangChain x Token Metrics setup is a big deal:
✅ AI That Acts
LangChain agents go beyond conversation—they can autonomously scan and analyze crypto markets using a suite of Token Metrics tools.
✅ Actionable Data
Token Metrics transforms complex market data into actionable insights, empowering the agent to support smarter trading and investment decisions.
✅ Current Market Analysis
Every time the agent runs, it draws on up-to-date Token Metrics data, ensuring responses reflect the latest market conditions.
✅ Fully Customizable
Tailor the agent to your needs, filter by DeFi tokens, set custom ROI thresholds, or incorporate additional data sources like social sentiment. The open-source codebase makes it easy to adapt the agent for any use case
What Can You Build With This?
This framework provides a versatile foundation for a wide range of crypto applications, including:
- Personal trading assistants
- Crypto Telegram bots
- LLM-integrated crypto dashboards
- Quant strategy testers
- AI-powered newsletters and daily briefs
By combining a powerful API with a reasoning engine, you unlock a new frontier in crypto intelligence.
Final Thoughts
The integration of Token Metrics with LangChain shows what’s possible when deep crypto analytics meets autonomous reasoning. Instead of flipping between dashboards, you can build an agent that does the research for you, surfaces profitable tokens, and delivers daily alpha—automatically.
Whether you’re a developer, trader, or AI enthusiast, this setup gives you a robust foundation to experiment, build, and push the future of AI trading forward.
Try It Yourself
Once the repository is public, you’ll be able to:
- Clone it from GitHub
- Add your API keys
- Customize your agent
- Start generating automated crypto insights today
Click here to view the demo.
AI agents are the future of trading—and with Token Metrics and LangChain, the future is already here.

Best Crypto Index in 2025: How AI-Powered Indices Redefine Crypto Trading?
The crypto market is rapidly evolving, and with it, the way investors approach asset allocation. Traditional token picking is being replaced by smarter, more diversified strategies like crypto indices. But as AI enters the scene, a new generation of indices—AI crypto indices—is emerging. So, what’s the difference? And which is better for investors in 2025?
In this guide, we break down the key differences, advantages, and use cases of crypto indices vs AI crypto indices, helping you decide which is better for your investment strategy.
What Are Crypto Indices?
A crypto index is a curated basket of cryptocurrencies grouped based on certain criteria such as market capitalization, sector (like DeFi or NFTs), or performance. Just like stock market indices (e.g., S&P 500), these indices offer passive exposure to a segment of the market, allowing investors to diversify without manually picking individual tokens.
Types of Crypto Indices:
- Market Cap Indices – Top 10, Top 25, or Top 100 coins by market cap
- Sector-Based Indices – DeFi, Gaming, Memecoins, RWA (Real World Assets), etc.
- Performance-Based Indices – Best-performing assets over a defined period
Crypto indices are typically rebalanced at regular intervals (e.g., weekly or monthly) and follow fixed rules.
What Are AI Crypto Indices?
AI crypto indices take things a step further by using artificial intelligence and machine learning models to dynamically manage the index.
Unlike static or rule-based crypto indices, AI crypto indices continuously analyze data—such as price action, sentiment, volume, momentum, and on-chain signals—to adjust holdings in real-time or near real-time.
Features of AI Crypto Indices:
- AI-Powered Rebalancing: Allocations change based on market signals, not fixed schedules
- Market Timing: Enter or exit positions when bullish or bearish conditions are detected
- Signal-Based Entry/Exit: Move to stablecoins when the AI model predicts a downturn
- Multi-Factor Analysis: Combines technical, fundamental, and sentiment indicators
Benefits of Traditional Crypto Indices
- Simplicity
Crypto indices are easy to understand and ideal for beginners who want broad exposure without analyzing charts. - Diversification
Instead of betting on one token, investors gain exposure to a group, reducing risk. - Low Maintenance
Once you invest, the portfolio is rebalanced automatically based on set rules. - Transparency
Rules and components are clear. You know what’s in your index and when it changes.
Benefits of AI Crypto Indices
- Smarter Market Timing
AI models detect bullish or bearish signals and adjust the portfolio accordingly—buying when momentum builds, selling when risk rises. - Higher Alpha Potential
By reacting faster to changing market conditions, AI indices often outperform static ones in volatile markets. - Dynamic Asset Allocation
Allocations aren’t fixed—they adapt based on hundreds of real-time data points like sentiment, on-chain activity, and volatility. - Built-in Risk Management
When bearish signals appear, AI indices can exit positions and shift to stablecoins—helping protect capital in downturns.
Which Is Better in 2025?
The answer depends on your investment style, risk tolerance, and goals:
Choose Crypto Indices if:
- You prefer a hands-off, passive approach
- You're a beginner looking for simple exposure
- You value transparency and low complexity
- You're investing for the long term regardless of market cycles
Choose AI Crypto Indices if:
- You want an actively managed experience without managing trades yourself
- You seek higher performance in volatile markets
- You want a strategy that adapts dynamically to real-time trends
- You care about downside protection during bear markets
In 2025, with markets becoming more data-driven and volatile, AI crypto indices are increasingly becoming the preferred option for both retail and institutional investors seeking a smarter way to invest.
Why Token Metrics AI Crypto Indices Stand Out
Token Metrics is at the forefront of AI-powered crypto investing. Its proprietary AI crypto indices use over 80 data points per token—including momentum, sentiment, on-chain trends, trading volume, and volatility—to construct and manage indices that enter and exit positions with precision.
- ✅ Bullish Signal? Capital is deployed into top-ranked tokens.
- ✅ Bearish Signal? The AI exits to stablecoins to reduce drawdowns.
- ✅ Real-Time Rebalancing? Yes—based on predictive indicators, not static rules.
Whether you're a trader looking for alpha or an investor looking to automate your exposure, Token Metrics AI crypto indices offer smart investing on autopilot.
Final Thoughts
In the debate of crypto indices vs AI crypto indices, there’s no one-size-fits-all answer. Traditional indices offer simplicity and passive diversification, while AI indices bring intelligence, agility, and risk-managed growth.
In 2025 and beyond, as crypto markets become more sophisticated, the edge will belong to those using smarter tools. AI crypto indices aren’t just the future—they’re the present.
FAQs
Q: Are AI crypto indices risky?
A: They’re typically less risky than picking individual tokens, thanks to built-in risk management and real-time adaptability.
Q: Can I customize an AI crypto index?
A: Platforms like Token Metrics are building toward more customizable AI-driven portfolios tailored to your preferences.
Q: Do AI indices outperform traditional indices?
A: In volatile markets, AI indices often outperform by reacting quicker to price swings and avoiding losses through bearish exits.
Q: Is this approach suitable for beginners?
A: Yes. AI crypto indices are designed to be user-friendly—offering the benefits of active trading without manual effort.
Want to experience the future of crypto investing?
Explore AI-powered indices now at Token Metrics.

Top Crypto Indices in 2025: The Best Ways to Invest in Crypto Without Picking Tokens
Crypto investors in 2025 face an overwhelming number of choices. With thousands of tokens, rapidly shifting narratives, and constant market volatility, building and managing a profitable portfolio isn’t easy. But one solution is gaining traction among both beginner and seasoned investors alike: crypto indices.
A crypto index is a curated basket of tokens that provides diversified exposure to a specific segment of the crypto market. Instead of researching and buying individual tokens, you invest in a single index that tracks a group of assets—similar to how the S&P 500 or NASDAQ works in traditional finance.
In this article, we’ll cover the top crypto indices in 2025, explain what makes each one stand out, and explore how AI is revolutionizing index investing in the crypto space.
What Is a Crypto Index?
A crypto index is a portfolio of cryptocurrencies selected and weighted using a specific methodology. It can be passive—holding the top 10 tokens by market cap—or active, where an algorithm or AI rebalances the index based on market conditions.
Investing in a crypto index means you’re buying into an entire theme or strategy, not just a single token. This helps reduce risk, smooth out returns, and simplify the investing process.
Why Use Crypto Indices in 2025?
Here’s why crypto indices are more relevant than ever in 2025:
- Diversification: Spread your capital across multiple tokens, reducing the impact of any single asset's volatility.
- Automation: Many indices rebalance automatically, saving you time and effort.
- Trend Exposure: Sector-based indices let you ride major trends like AI, DeFi, or Real World Assets (RWA).
- Risk Management: AI-powered indices can reduce exposure or shift to stablecoins in bearish conditions.
Top Crypto Indices in 2025
1. Token Metrics AI Indices
- Type: Actively Managed
- Technology: AI-driven with over 80 data points per token
- Themes: Memecoins, RWA, AI Agents, DeFi, Layer 1s
- Frequency: Rebalanced weekly based on bullish/bearish market signals
Why It’s a Top Pick:
Token Metrics has pioneered a new generation of crypto indices that actively trade based on AI insights. Instead of static rebalancing, the AI identifies when to enter or exit tokens based on current momentum, volatility, sentiment, and technical indicators. These indices offer a smarter, automated approach to outperforming the market—especially in fast-moving sectors like AI tokens or memecoins.
2. Bitwise 10 Crypto Index Fund (BITW)
- Type: Passive
- Structure: Traditional investment vehicle (available via brokerage)
- Assets: Top 10 cryptocurrencies by market cap
Why It’s a Top Pick:
BITW is ideal for investors looking for simple, long-term exposure to the largest and most established cryptos. It tracks the performance of the top 10 digital assets, including Bitcoin (BTC), Ethereum (ETH), and Solana (SOL). It's fully regulated and targets institutions or traditional investors entering crypto.
3. Phuture DeFi Index (PDI)
- Type: On-chain, Passive
- Focus: Decentralized Finance (DeFi) tokens
- Access: Non-custodial, DeFi-native
Why It’s a Top Pick:
Phuture makes index investing seamless within DeFi ecosystems. Its DeFi Index provides exposure to high-utility tokens like AAVE, UNI, and CRV. Ideal for crypto-native users, it’s completely on-chain, composable, and doesn’t require intermediaries.
4. Index Coop – GMI (Bankless DeFi Innovation Index)
- Type: Community-Governed, Thematic
- Focus: Experimental and innovative DeFi projects
- Governance: Managed by Index Coop and Bankless DAO
Why It’s a Top Pick:
GMI stands for “Going Mainstream Index” and aims to capture cutting-edge projects at the bleeding edge of DeFi innovation. It’s great for those bullish on next-gen financial infrastructure and looking for exposure to governance tokens, staking protocols, and experimental finance.
5. Crypto20 (C20)
- Type: Tokenized Index Fund
- Composition: Top 20 cryptocurrencies
- Access: ERC-20 token (C20) represents index share
Why It’s a Top Pick:
Crypto20 was one of the first tokenized crypto index funds. It lets you invest in the top 20 cryptocurrencies through a single token, with auto-rebalancing and transparent weighting. It’s an easy on-ramp for beginners who want broad crypto exposure.
6. Token Metrics Global Market Cap Indices (HODL Series)
- Type: Passively Managed
- Available Indices: Top 5, 10, 25, and 100 by market cap
- Strategy: Buy-and-hold portfolios for long-term investors
Why It’s a Top Pick:
These indices are designed for investors who believe in the long-term growth of the crypto market but don’t want to chase narratives. The HODL series is great for passive wealth accumulation with minimal trading activity.
Thematic Crypto Indices to Watch
If you’re looking to ride specific crypto narratives in 2025, these thematic indices are worth considering:
🔹 AI Tokens Index
- Tracks top AI-focused crypto projects like FET, AGIX, and GRT.
- Surging interest due to the AI boom in both tech and crypto sectors.
🔹 Memecoin Index
- Includes high-volatility meme tokens like DOGE, PEPE, BONK, and WIF.
- Great for traders who want to play high-risk, high-reward cycles.
🔹 RWA Index (Real World Assets)
- Exposure to tokens that represent off-chain value: MKR, ONDO, XDC, etc.
- Benefiting from institutional crypto adoption and tokenized finance growth.
🔹 Layer 1 Index
- Tracks the performance of top blockchain platforms: ETH, SOL, AVAX, NEAR, etc.
- Best for investors bullish on infrastructure plays.
How to Start Investing in Crypto Indices
- Choose a Platform – Token Metrics, Bitwise, Index Coop, or Phuture.
- Select an Index – Based on your interest: AI, DeFi, Memecoins, or Market Cap.
- Connect Wallet or Sign Up – Depending on whether it's on-chain or centralized.
- Fund Your Account – Typically via USDC, ETH, or fiat.
- Monitor Performance – AI indices may require weekly check-ins; HODL indices can be set and forgotten.
Final Thoughts: Crypto Indices Are the Smartest Way to Invest in 2025
Whether you’re a new investor or an experienced trader, crypto indices in 2025 offer one of the most efficient, diversified, and intelligent ways to grow your crypto portfolio. Platforms like Token Metrics lead the way with cutting-edge AI-powered indices, while more traditional players like Bitwise provide reliable exposure for institutional strategies.
By investing in an index, you’re not just buying a few coins—you’re gaining access to a curated, balanced, and often smarter portfolio that evolves with the market. And as AI and automation take over more of the investing process, index strategies are becoming even more powerful.
If you’re ready to stop guessing and start investing strategically, now is the time to explore the best crypto indices available.

What Are Crypto Indices? A Complete Guide to Crypto Index and AI Crypto Indices
As the cryptocurrency market matures, new tools are emerging to help investors navigate its volatility and complexity. One of the most powerful innovations in this space is the crypto index—a way to simplify crypto investing, reduce risk, and gain exposure to top-performing tokens without having to pick winners manually. Even more exciting is the rise of AI-powered crypto indices, which bring data science and machine learning into the equation to make smarter, real-time portfolio decisions.
In this article, we’ll break down everything you need to know about crypto indices, including:
- What is a crypto index?
- How do crypto indices work?
- Benefits of crypto index investing
- The evolution of AI crypto indices
- Best platforms offering crypto index solutions
- How to start investing in crypto indices
What Is a Crypto Index?
A crypto index is a curated basket of cryptocurrencies that represents a particular theme, strategy, or market segment. Just like traditional stock market indices such as the S&P 500 or NASDAQ-100, a crypto index helps investors track the performance of a group of assets, rather than betting on just one token.
For example, a Top 10 Market Cap Crypto Index would include the ten largest cryptocurrencies by market capitalization (such as Bitcoin, Ethereum, Solana, etc.), and the index’s performance reflects the collective movement of these assets.
Types of Crypto Indices
- Market Cap Indices – Track the top cryptocurrencies by total market value.
- Thematic Indices – Focus on specific sectors like DeFi, AI, Gaming, Memecoins, or Layer-1s.
- Strategy-Based Indices – Include actively managed or algorithm-driven portfolios.
- Yield Indices – Target assets offering staking rewards or yield farming income.
How Do Crypto Indices Work?
Crypto indices are built using a defined methodology that selects, weights, and periodically rebalances assets within the index. Some use fixed rules (e.g., market cap weighting), while others apply more dynamic strategies based on trading signals or AI models.
Key Components:
- Constituent Selection: Tokens are selected based on criteria like market cap, volume, or sector.
- Weighting Method: Each token’s proportion in the index (e.g., equally weighted, cap-weighted).
- Rebalancing: The portfolio is adjusted regularly (weekly, monthly) to reflect market changes.
- Performance Tracking: The index value changes over time to show how the portfolio performs.
Investors can gain exposure to these indices via platforms that either simulate index performance or allow on-chain index purchases through tokenized portfolios.
Benefits of Investing in a Crypto Index
Investing in a crypto index offers multiple benefits—especially for those who want exposure to the crypto market without actively trading.
1. Diversification
Indices reduce the risk of putting all your capital into one volatile asset. Even if one token underperforms, others can balance it out.
2. Simplicity
No need to research every project. Indices package top tokens into a single product that reflects a broader market or theme.
3. Risk Management
Rebalancing and rules-based strategies prevent overexposure to risky or declining assets.
4. Long-Term Growth
Over time, diversified portfolios tend to outperform manual picks due to compounding and market-wide exposure.
5. Passive Investing
Crypto indices are ideal for “set and forget” strategies. Let the index work while you focus on your long-term goals.
What Are AI Crypto Indices?
AI crypto indices take the concept of index investing to the next level. Instead of using static rules, these indices rely on machine learning algorithms to analyze real-time market data and adjust the portfolio dynamically.
How It Works:
- AI scans 80+ data points per token: price action, momentum, sentiment, volatility, volume, technical indicators, and more.
- It generates trading signals (bullish or bearish) for each token.
- The index automatically allocates capital into assets with strong bullish signals.
- When market conditions turn bearish, the AI exits positions into stablecoins to preserve capital.
- Portfolios are updated weekly or even daily for maximum responsiveness.
AI crypto indices are ideal for those who want smart, automated crypto trading without the hassle of constant monitoring.
Why AI-Powered Indices Are the Future of Crypto Investing
The crypto market is 24/7 and moves fast. Human traders can't keep up with all the news, charts, and patterns—but AI can.
Key Advantages of AI Indices:
- Faster Response: AI reacts instantly to market trends and news.
- Data-Driven Decisions: No emotional bias—just pure analytics.
- Backtested Models: AI strategies can be tested against years of historical data.
- Dynamic Risk Management: AI shifts capital to safety during downtrends.
- Better ROI Potential: AI indices often outperform simple HODL portfolios.
Best Platforms Offering Crypto Indices
Several platforms now offer crypto index investing. Some focus on passive HODL-style indices, while others provide AI-managed strategies.
Top Picks:
- Token Metrics AI Indices: Offers active AI-driven indices that rebalance weekly based on bullish/bearish signals. Includes categories like Memecoins, DeFi, RWA, AI, and Top Market Cap.
- Bitwise: Traditional-style index funds for institutional investors.
- Phuture: On-chain indices that users can invest in directly from their crypto wallets.
- Index Coop: Community-governed crypto index products built on Ethereum.
Crypto Index AI Trading - Coming soon on Token Metrics
How to Start Investing in a Crypto Index
Step 1: Choose Your Platform
Select a platform that offers indices aligned with your goals—passive, thematic, or AI-based.
Step 2: Select an Index
Pick an index based on your interest (Top 10, DeFi, AI tokens, etc.).
Step 3: Connect Wallet / Create Account
Some platforms are on-chain (Web3), others use custodial models.
Step 4: Allocate Capital
Fund your account or wallet with USDC, ETH, or BTC.
Step 5: Monitor Performance
Check your index portfolio’s performance weekly. With AI indices, much of the work is automated.
Final Thoughts: Crypto Indexing Is Smart Investing
Crypto indices are reshaping the way people invest in digital assets. Whether you’re a beginner or seasoned trader, index investing offers a powerful blend of diversification, simplicity, and smart automation. And with the rise of AI-powered indices, investors can now access hedge-fund level strategies at the click of a button.
If you want to invest smarter and trade less, crypto indices—especially AI crypto indices—are the future. They’re not just tools for passive exposure—they’re intelligent systems designed to maximize returns and minimize risks in the wild world of crypto.

Top Crypto Newsletters in 2025: Stay Ahead with the Best Crypto Daily Insights
In the fast-paced world of cryptocurrency, staying informed can mean the difference between seizing a major opportunity and missing it entirely. In 2025, the best way to stay on top of crypto trends, altcoin picks, and market analysis is through expertly curated crypto newsletters. These newsletters offer a steady stream of actionable insights, expert commentary, and research-backed predictions—delivered straight to your inbox.
Whether you're a seasoned investor, a crypto founder, or just a curious learner, subscribing to the right newsletters can supercharge your understanding of the market and help you make better decisions.
In this blog, we’ll highlight the top crypto newsletters in 2025, with an in-depth look at what makes each one valuable. We’ll also explore why the Token Metrics Daily Newsletter stands out as a must-have resource for over 150,000 active subscribers.
Why Crypto Newsletters Still Matter in 2025
Despite the growth of Twitter, Telegram, and Discord communities, newsletters remain the most curated, distraction-free format for staying informed. Here’s why top investors still rely on email newsletters in 2025:
- Signal Over Noise: Unlike social feeds, newsletters deliver only the most relevant insights.
- Expert Commentary: Many newsletters are written by top-tier analysts, developers, or traders.
- Regularity and Consistency: They arrive at a set frequency—daily, weekly, or monthly—making them easy to follow.
- Research-Based: Many crypto newsletters are data-driven, referencing on-chain activity, technical analysis, and AI-powered research.
Now let’s dive into the top newsletters dominating the crypto space in 2025.
1. Token Metrics Daily Newsletter
📩 Frequency: Daily
🧠 Focus: AI-Powered Market Insights, Token Ratings, Investment Research
👥 Subscribers: 150,000+
The Token Metrics Daily Newsletter is one of the most trusted and widely read publications in the crypto industry. Written by a team of crypto quants, analysts, and investment researchers, the newsletter provides a daily breakdown of:
- Top-performing tokens
- AI-generated Bullish and Bearish signals
- Market Sentiment Analysis
- Trader and Investor Grade insights
- New altcoin picks
- Sector-level performance (AI, RWA, DeFi, Memecoins, etc.)
Each issue blends quantitative data with expert interpretation, making it incredibly valuable whether you're a casual investor or managing a professional portfolio.
Token Metrics’ proprietary AI grades over 6,000 tokens and scans the market for shifts in risk/reward, price momentum, and narrative strength. This cutting-edge data is broken down and interpreted in the daily newsletter, giving readers a significant informational edge before markets move.
Why It’s Great:
- Quant research distilled into readable insights
- Actionable signals with clear reasoning
- Trusted by traders, hedge funds, and VC-backed startups
Token Metrics isn’t just a newsletter — it’s a complete crypto intelligence platform. If you’d like a walkthrough of how to use it effectively, book a call with us here.
2. The Defiant
📩 Frequency: Daily
🧠 Focus: DeFi News, Governance, Protocol Deep Dives
👥 Subscribers: 100,000+
The Defiant is the go-to resource for everything DeFi. Launched by journalist Camila Russo, it has grown into a full-fledged media brand with a daily newsletter that delivers news, DeFi protocol updates, governance votes, liquidity shifts, and analysis of the decentralized finance space.
In 2025, the newsletter continues to dominate in terms of original reporting, exclusive interviews, and early alerts about rising DeFi projects or regulatory changes.
Why It’s Great:
- Sharp editorial focus on DeFi
- Excellent context around protocol changes
- Balances technical accuracy with readability
3. Alpha Please
📩 Frequency: Daily
🧠 Focus: On-chain Metrics, Narratives, Emerging Projects
👥 Subscribers: ~80,000–120,000
Alpha Please is one of the fastest-growing newsletters in 2025, known for its data-driven approach and sharp narrative tracking. Every edition focuses on what’s working on-chain—including wallet activity, TVL shifts, token unlocks, and momentum narratives like AI tokens or RWAs.
It distills complexity into clarity, often combining on-chain analytics with sectoral insights across Ethereum, Solana, and newer L1s.
Why It’s Great:
- Excellent coverage of “early narrative rotations”
- Features wallet tracking and token unlock analysis
- Targets power users without being overwhelming
4. CoinSnacks
📩 Frequency: Weekly
🧠 Focus: Crypto News Recap, Regulation, Adoption
👥 Subscribers: 80,000+
CoinSnacks is ideal for the casual crypto enthusiast or early-stage investor who wants a digestible weekly roundup of the most important stories. It balances crypto adoption news, regulatory developments, and token updates in a short and readable format.
With sections like "This Week’s Snacks" and "Chart of the Week", CoinSnacks makes staying informed simple and light.
Why It’s Great:
- Concise and beginner-friendly
- Excellent for catching up once a week
- Good balance of news, commentary, and charts
5. Wolf Den Research
📩 Frequency: 3–4x Weekly
🧠 Focus: Token Deep Dives, Risk Analysis, Undervalued Gems
👥 Subscribers: ~50,000–75,000
Wolf Den stands out for its in-depth token research and valuation breakdowns. It’s favored by readers who are long-term investors or those who want to spot undervalued tokens before they pump. Unlike hype-based newsletters, it emphasizes risk-adjusted analysis and sustainability of growth.
Often, their research overlaps with projects that Token Metrics grades highly, making it a solid complementary source.
Why It’s Great:
- High-conviction, low-frequency publishing model
- Great for long-term thesis-building
- Trusted by boutique crypto funds and serious retail investors
6. Messari Unfiltered
📩 Frequency: Daily
🧠 Focus: Institutional Analysis, Token Valuations, Research Reports
👥 Subscribers: 60,000+
Messari is a respected name in institutional crypto research, and their daily newsletter, Unfiltered, brings that depth to your inbox. It’s packed with token valuations, funding announcements, DAO metrics, and governance proposals.
Perfect for professionals, founders, or analysts looking for rigorous coverage, Messari’s newsletter often links to deeper research pieces that are widely cited in the industry.
Why It’s Great:
- Deep-dive token research and valuations
- Strong emphasis on data integrity
- Institutional-grade insights made accessible
7. TLDR Crypto
📩 Frequency: Daily
🧠 Focus: Daily News Summaries, Token Launches, Ecosystem Updates
👥 Subscribers: 50,000+
TLDR Crypto focuses on summarizing each day’s key crypto developments in one quick email. It covers everything from token announcements and blockchain upgrades to hacks and VC raises.
It’s great for professionals who need to stay informed but have limited time to scan through social media or read multiple news sites.
Why It’s Great:
- Extremely time-efficient
- No-fluff format
- Covers a broad range of topics daily
Choosing the Right Newsletter for You
NewsletterBest ForToken MetricsQuantitative traders, serious investorsThe DefiantDeFi natives, DAO participantsBanklessEthereum and L2 enthusiastsCoinSnacksCasual investors, beginnersMilk RoadMeme lovers, quick readersMessariProfessionals and institutionsTLDR CryptoBusy readers, quick digest seekers
Final Thoughts
In 2025, crypto newsletters remain one of the best ways to stay informed, sharpen your trading strategy, and build conviction in your investments. Whether you’re deep into DeFi or just want to know which altcoin is trending today, there’s a newsletter for you.
And if you’re looking for daily, AI-backed crypto research that cuts through the noise, the Token Metrics Daily Newsletter is an essential tool in your arsenal. With powerful insights, expert analysis, and real-time signals, it helps over 150,000 subscribers stay one step ahead of the market every day.
Subscribe to the Token Metrics Newsletter
📬 https://research.tokenmetrics.com/
Because in crypto, timing isn’t everything—it’s the only thing.

Unlock AI Crypto Trading: Token Metrics Crypto API Integration with QuickNode
The world of crypto trading is evolving fast, and access to real-time AI-driven data is becoming critical for both individual traders and developers building crypto applications. Token Metrics, a leading AI-powered crypto trading and analytics platform, has taken another giant leap by integrating with QuickNode, a cutting-edge blockchain infrastructure provider. This integration enables developers and crypto enthusiasts to access Token Metrics’ powerful trading signals, grades, and reports directly through QuickNode’s robust API marketplace.
In this article, we’ll walk you through how the Token Metrics API works on QuickNode, how to set it up, and why this partnership is a game-changer for anyone serious about crypto trading or building crypto applications.
Why Token Metrics Integration with QuickNode Matters
Before we dive into the setup process, let’s understand why this integration is so valuable.
Token Metrics uses advanced AI models that analyze over 80 data points across thousands of crypto assets. These models generate actionable insights, including:
- Trader Grades: Short-term performance outlooks
- Investor Grades: Long-term performance assessments
- AI Trading Signals: Real-time buy/sell signals based on market conditions
- AI Agents & Reports: In-depth analysis generated by autonomous AI agents
With the QuickNode integration, developers and traders can now directly access this rich dataset through a simplified, scalable API infrastructure, without worrying about backend complexity.
Step-by-Step: How to Set Up Token Metrics API on QuickNode
Setting up Token Metrics API endpoints via QuickNode is remarkably straightforward. Here’s how you can start pulling real-time trading signals into your application or trading dashboard:
1️⃣ Create a New Endpoint
First, log in to your QuickNode account. In the Endpoints section, click on Create New Endpoint. You will be prompted to select a base chain. For this example, we’ll select Base Mainnet — QuickNode's high-performance blockchain infrastructure designed for speed, scalability, and reliability.
After selecting the chain, click Continue to move to the next step.
2️⃣ Select Your Token Metrics API Plan
QuickNode offers multiple Token Metrics API subscription plans based on your needs:

For this setup, let’s choose the Basic Plan, which provides 5,000 API calls per month along with access to Trader Grades — ideal for developers just starting out or small-scale projects.
Once you’ve selected your plan, proceed to checkout and click Complete Purchase.
3️⃣ Retrieve and Apply Your API Key
After purchasing your Token Metrics API subscription, QuickNode will generate your endpoint URL and API key. This is where the integration gets incredibly developer-friendly.
Go to the Add-Ons > Getting Started section, copy the provided endpoint code, and paste it into your project’s codebase. Assign a title to the key for easy reference — for example, you might name it Token ID — and provide the specific token identifier. In this case, for Bitcoin, you would set its value to 3375.
Once set up, simply click Send to initiate your first request.
4️⃣ Access Real-Time Trading Signals
The Trading Signals Endpoint is one of the most powerful tools available through the Token Metrics API. For each token you query, the endpoint returns daily trading signals, allowing you to:
- See whether the AI recommends buying or selling
- Analyze signals based on real-time market data
- Use these insights to improve your trading decisions or power your crypto applications
For example, when querying Bitcoin, the Token Metrics API will deliver the most up-to-date trading recommendation based on AI analysis of price movements, technical indicators, sentiment analysis, and on-chain data.
5️⃣ Monitor Live Metrics
Once you start pulling data from the API, you’ll be able to monitor live trading signals via your integrated dashboards or trading tools. This real-time data empowers traders to make smarter, more timely decisions while offering developers a new layer of predictive analytics for their crypto platforms.
With minimal code, you can embed Token Metrics’ proprietary AI-driven metrics into:
- Trading bots
- Portfolio trackers
- Crypto dashboards
- Market intelligence platforms
- Educational apps
The Power of AI Crypto Trading at Your Fingertips
What makes this integration unique is Token Metrics’ AI-first approach to crypto analysis. Unlike basic data aggregators, Token Metrics leverages machine learning models trained on:
- Price action
- Technical indicators
- On-chain activity
- Market sentiment
- Macroeconomic trends
This allows the system to generate forward-looking signals, not just lagging indicators — a massive advantage for crypto traders who need to stay ahead of volatile market swings.
Benefits for Developers
The integration with QuickNode isn’t just for active traders — it’s a huge win for developers building crypto products:
- Faster Time-to-Market: No need to build complex analytics models from scratch.
- Scalability: QuickNode handles the backend infrastructure, while Token Metrics handles the AI data.
- Customizable API Usage: Tailor your subscription level based on how much data your app needs.
- Enterprise-Grade Reliability: QuickNode’s low-latency infrastructure ensures your app stays fast and stable.
Whether you're building for retail traders, institutions, or crypto communities, this API integration lets you deliver AI-powered insights quickly.
Unlock the Future of Crypto Trading
The Token Metrics integration with QuickNode represents the next evolution in crypto market intelligence — combining AI-powered predictive analytics with world-class blockchain infrastructure. Developers can now easily embed Token Metrics’ actionable trading signals into their applications, while traders can make smarter, data-driven decisions.
If you’re serious about building cutting-edge crypto products or improving your personal trading strategies, this integration offers you the most advanced AI tools available — ready to deploy within minutes.
Click here to view the demo!
👉 Start today by integrating Token Metrics API via QuickNode and unlock AI-powered crypto trading.
Frequently Asked Questions (FAQ)
Q: Do I need to be a developer to use Token Metrics API via QuickNode?
A: While some technical knowledge is helpful, QuickNode’s user-friendly interface makes it easy to set up endpoints even if you’re not a full-time developer.
Q: Can I upgrade my Token Metrics plan later?
A: Yes. You can start with any plan and upgrade as your needs grow.
Q: What kind of data does the API provide?
A: Trader Grades, Investor Grades, AI Trading Signals, Token Reports, AI Agent Reports, and much more depending on your subscription tier.
Q: Can I use this for building trading bots?
A: Absolutely. Many developers integrate Token Metrics data directly into automated trading bots to execute AI-informed strategies.

AI Crypto Trading: Token Metrics Bullish & Bearish Signals Explained 2025
In the world of cryptocurrency trading, timing isn’t just important — it’s everything.
Buying too early ties up valuable capital. Buying too late means you miss the explosive moves that define crypto trading cycles. That’s why serious traders in 2025 are moving beyond basic technical analysis and adopting advanced AI crypto trading tools that deliver real-time precision.
At the forefront of this evolution is Token Metrics, a leading AI-powered crypto trading platform. Its Bullish and Bearish Signals, driven by cutting-edge AI cryptocurrency trading algorithms, are providing traders with an unprecedented edge — outperforming legacy indicators like RSI, MACD, trendlines, and other traditional tools.
In this detailed guide, we’ll explore exactly how these signals work, why they’re so effective, and how they’re helping traders dominate the crypto trading markets with confidence and clarity.
What Are Token Metrics Bullish and Bearish Signals?
Token Metrics has developed a proprietary system that generates Bullish and Bearish signals across thousands of crypto assets. Unlike simplistic price-based indicators, these signals are built on a sophisticated multi-factor model that combines:
- Price momentum shifts
- Trading volume spikes
- Support and resistance levels
- On-chain activity strength
- Whale wallet flows
- Sentiment analysis
- Historical pattern recognition
- Liquidity and order book depth
Each signal is generated when multiple independent factors align — a process known as signal confluence. This drastically reduces false positives and ensures that only high-probability setups trigger alerts.
In simple terms: Token Metrics Bullish and Bearish Signals don’t trigger based on one factor — they fire when multiple critical data points confirm the setup. This makes them far more reliable than most tools used in traditional cryptocurrency trading.
The AI Advantage: Why These Signals Are Different
What sets Token Metrics apart from standard crypto trading indicators is its heavy use of artificial intelligence (AI) and machine learning models that analyze real market behavior.
Traditional Tools Are Lagging
Popular indicators like RSI (Relative Strength Index) and MACD (Moving Average Convergence Divergence) have been staples of cryptocurrency trading for years. But they share one fatal flaw: they are lagging indicators. They only react after price movements have already occurred.
This delay often causes traders to enter late, miss opportunities, or fall into bull traps right before reversals.
Token Metrics Signals Are Forward-Looking
In contrast, Token Metrics AI Signals are trained on outcomes, not just patterns. The AI models analyze:
- How thousands of past price patterns played out
- Which combinations of factors led to real breakouts or breakdowns
- Which setups frequently produced false signals historically
By learning from historical market outcomes, the AI constantly refines its signal generation, adapting to ever-changing cryptocurrency trading conditions. This adaptability makes the system market responsive, something static indicators like RSI or MACD can’t achieve.
AI Validation & Backtesting
Every signal generated by Token Metrics is validated using AI-powered backtesting. This allows the system to continuously test its models against massive historical datasets, ensuring the signals remain accurate across different market regimes — whether it’s bull markets, bear markets, or sideways ranges.
The end result: a real-time AI cryptocurrency trading system that constantly evolves and improves its accuracy.
Real-World Examples: Token Metrics Signals in Action
During a recent webinar, the Token Metrics team showcased multiple real-world examples of how its Bullish and Bearish Signals outperformed traditional indicators.
Example 1: $DEGEN
- A Bullish Signal was triggered on $DEGEN before a major +35% breakout.
- At the time of signal activation, there was no traditional RSI divergence or MACD cross.
- Traders using Token Metrics entered early, while those relying on standard tools were still waiting for confirmation.
Example 2: $ENA
- A Bearish Signal was triggered on $ENA ahead of a -22% price correction.
- Again, standard technical indicators provided no early warning.
- Traders using AI crypto trading signals were able to exit before the sharp drop.
These examples highlight how AI-powered crypto trading systems offer traders an advantage — not by predicting the future perfectly, but by identifying statistically high-probability setups before they become obvious to the rest of the market.
How Traders Use Token Metrics Signals in Cryptocurrency Trading
The flexibility of Token Metrics signals allows traders across multiple strategies to integrate them into their trading workflows.
1. Signal Confirmation with Trader Grades
Many traders first screen for high Trader Grade tokens (another proprietary AI scoring model within Token Metrics) and then use Bullish or Bearish Signals for entry and exit timing confirmation.
2. Real-Time Alerts
Traders set real-time alerts on specific tokens. When a signal fires, they receive instant notifications via the platform, web app, or API — allowing them to act immediately.
3. Backtesting & Historical Performance
Token Metrics provides overlays on price charts that visually display previous signal triggers. Traders can easily backtest how signals performed historically, building trust in the system’s accuracy.
4. Algorithmic Bot Integration
For advanced users and developers, Token Metrics provides full API access. This allows algorithmic traders and fund managers to integrate Bullish and Bearish Signals directly into automated AI crypto trading bots for fully systematic execution.
Bullish vs Bearish: What Do These Signals Actually Mean?
Bullish Signal
- Multiple AI-validated factors align to suggest that price momentum, volume expansion, sentiment, and technical structure are primed for an upside breakout.
- Signals early momentum shifts before retail traders notice.
Bearish Signal
- Signals deterioration in momentum, liquidity weakening, profit-taking behavior, and increased downside risk.
- Often triggers before obvious technical breakdowns occur.
Unlike basic indicators that react late, these signals give you early actionable intelligence — exactly what’s needed in highly volatile cryptocurrency trading markets.
Token Metrics AI Signals vs Traditional TA Indicators
Feature Token Metrics AI Signals RSI / MACD / Traditional TA
AI-trained on historical outcomes ✅ Yes ❌ No
Multi-factor confluence (80+ data points) ✅ Yes ❌ No
Adaptive to changing market conditions ✅ Dynamic ❌ Static
Intraday real-time updates ✅ Yes ❌ Often delayed
API integration for automated trading ✅ Yes ❌ No
In short: Token Metrics AI Signals give you a probabilistic edge that traditional technical analysis simply can’t offer.
Who Benefits Most from AI Cryptocurrency Trading Signals?
AI-powered Bullish and Bearish Signals can be game-changing for a wide variety of cryptocurrency trading participants:
- Day Traders: Time breakouts early and manage risk efficiently.
- Swing Traders: Identify narrative shifts and sector rotations before price expansion.
- Algorithmic Bot Builders: Feed signals directly into AI crypto trading bots for systematic execution.
- Fund Managers: Avoid drawdowns and rebalance portfolios with quant-level precision.
- Long-Term Investors: Exit fading trends early and reallocate into stronger narratives.
Whether you’re an active trader or a long-term crypto investor, having AI-driven signals at your fingertips gives you a competitive advantage over the majority of traders still relying on outdated, lagging tools.
The Future of Cryptocurrency Trading Is AI-Powered
The cryptocurrency markets have evolved dramatically. In 2025, AI crypto trading is no longer a luxury for large institutions — it’s quickly becoming the standard for serious crypto traders.
- Markets are faster.
- Narratives rotate quicker.
- Capital flows shift hourly.
- Manual chart watching is increasingly obsolete.
With Token Metrics Bullish and Bearish Signals:
- You trade data, not emotion.
- You follow probability, not predictions.
- You respond to real-time conditions instead of reacting late.
In a space where being early is everything, AI cryptocurrency trading delivers the edge traders need to stay profitable in both bull and bear markets.
Conclusion
Crypto trading in 2025 demands smarter tools. Token Metrics Bullish and Bearish Signals represent a major breakthrough in AI crypto trading technology, providing traders with real-time, actionable intelligence that beats traditional indicators.
By combining deep AI analysis, multi-factor modeling, and continuous backtesting, Token Metrics offers one of the most advanced cryptocurrency trading systems available today.
If you want to trade with greater precision, avoid costly mistakes, and stay ahead of volatile market shifts, AI crypto trading signals from Token Metrics are your new secret weapon.

AI Crypto Trading: Token Metrics Real-Time AI Grades for Crypto Trading
The cryptocurrency trading landscape moves at lightning speed. Tokens pump, narratives shift, and entire sectors rotate overnight. In this chaotic environment, traders need more than just basic charts and lagging indicators — they need real-time, data-driven tools that can process vast amounts of information instantly.
That’s exactly where AI crypto trading comes in. In 2025, Token Metrics has taken cryptocurrency trading to a new level with its advanced Real-Time AI Grades, giving both traders and investors a clear edge in the hyper-volatile crypto trading markets.
With AI-powered Trader and Investor Grades, Token Metrics helps users evaluate any token’s strength, momentum, and long-term trend alignment — all calculated in real-time using over 80 data points. This isn’t just data. It’s actionable intelligence, powered by AI cryptocurrency trading models designed for today’s fast-moving market.
What Are Token Metrics Real-Time AI Grades?
At the core of Token Metrics' AI crypto trading platform are two proprietary grading systems:
1. Trader Grade
- Focuses on short-term price action and momentum.
- Designed for swing traders, active traders, and short-term speculators.
- Measures rapid changes in volatility, volume, trend strength, and technical setups.
- Helps traders identify tokens with breakout potential before they take off.
2. Investor Grade
- Focuses on long-term trend sustainability.
- Ideal for long-term holders, portfolio managers, and fundamental investors.
- Evaluates trend alignment, strength of price structure, and on-chain sustainability.
- Helps investors avoid weak tokens and stay positioned in strong long-term performers.
Both grades are calculated using over 80 quantitative and on-chain data points that are continuously updated. These data points include:
- Volatility metrics
- Liquidity and volume trends
- RSI divergences
- On-chain transaction activity
- Relative strength vs Bitcoin and Ethereum
- Order book dynamics
- Sentiment analysis
- Whale wallet flows
- Exchange inflows/outflows
The grades are expressed on a simple 0 to 100 scale, making it easy for traders to quickly assess a token’s strength. In most cases, a Trader Grade above 90 signals that a token is showing breakout potential, while a falling Investor Grade can warn of an impending trend reversal.
In short, Token Metrics uses AI cryptocurrency trading technology to distill massive data into simple, actionable grades — making cryptocurrency trading far more data-driven and precise.
Real-Time AI Grading: The New Standard for Crypto Trading
Until recently, these grades were updated daily. But now, Token Metrics has moved to real-time grading for high-volume tokens, creating a breakthrough moment for AI crypto trading.
What real-time AI grading means for crypto traders:
- Intraday Adjustments: Grades now update throughout the day based on real-time price movements, volume surges, and market volatility shifts.
- Early Breakout Detection: Traders receive breakout signals early — often before major price moves hit social media or mainstream attention.
- Risk-Off Alerts: Investor Grades drop as long-term trends weaken, providing timely warnings to exit positions before steep corrections occur.
With real-time grading, these AI crypto trading signals are no longer simply informative — they’re fully actionable. Traders can now respond to shifts in momentum as they happen, not after the move has already played out.
Live Use Case: Real-Time Grades in Action
During a recent Token Metrics webinar, the power of real-time AI grading was demonstrated with live market examples:
- The Trader Grade flagged a high score on $NORMIE just before a 40% intraday move. Traders who acted on the signal caught the breakout early.
- Simultaneously, the Investor Grade on $TNSR began to drop, signaling weakening long-term strength — a clear sign to rotate out and avoid potential downside.
This real-time grading system gives traders an enormous edge in cryptocurrency trading. Instead of reacting emotionally to price moves, traders can confidently follow objective AI-powered signals.
Visual Overlays: Making AI Crypto Trading Clearer Than Ever
One of the most powerful features of Token Metrics Real-Time Grades is the overlay integration on live price charts within the platform.
With visual overlays, traders can:
- Instantly see when grades peak or drop.
- Correlate grading signals with live price action.
- Visually backtest how grades behaved during previous trends.
- Clearly identify when a token’s momentum flips from bullish to bearish.
This creates a visual roadmap for crypto trading — allowing users to instantly read the health of any token’s trend with unparalleled clarity. For AI crypto trading, this level of real-time visual feedback dramatically improves confidence and precision.
Token Metrics AI Grades vs Traditional Crypto Trading Indicators
Traditional cryptocurrency trading indicators like RSI, MACD, and basic chart patterns have major limitations:
Feature Token Metrics AI Grades Traditional TA Tools
Combines 80+ real-time data points ✅ Yes ❌ No
AI-powered signal generation ✅ Yes ❌ No
Real-time intraday updates ✅ Yes ❌Often delayed
Visual chart overlays ✅ Yes ❌ Manual
Integrated filtering & automation ✅ Yes ❌ Lacks automation
While traditional indicators rely on simplistic price-based formulas, Token Metrics combines multi-dimensional data sources with AI modeling. This is the future of AI cryptocurrency trading — far more comprehensive, adaptive, and responsive than old-school technical analysis.
Who Should Use Token Metrics AI Grades?
The beauty of real-time AI grading is that it’s highly adaptable across different types of cryptocurrency traders and investors:
- Day Traders & Swing Traders: Spot breakout candidates early based on rapid Trader Grade spikes.
- Algorithmic Strategy Builders: Feed real-time grading data into automated AI crypto trading bots for highly responsive execution.
- Fund Managers & Portfolio Analysts: Vet tokens for long-term allocations using Investor Grades and trend alignment.
- Crypto Research Analysts: Monitor sector strength, narrative shifts, and capital rotations based on aggregate grades.
- Token Metrics API Developers: Integrate AI grading data directly into custom crypto trading dashboards and bots.
If you care about momentum, timing, filtering, and precision in cryptocurrency trading, these grades offer one of the strongest data-driven edges available in the market today.
Why AI Crypto Trading Is the Future of Cryptocurrency Trading
The cryptocurrency market is simply too fast, too global, and too emotional for purely manual trading. Attention shifts hourly. Liquidity floods into narratives instantly. Retail and institutional money rotate rapidly between sectors.
AI crypto trading is the only way to stay ahead of this chaos.
With Token Metrics’ Real-Time AI Grades:
- Traders don’t need to monitor hundreds of charts 24/7.
- Emotions and guesswork are replaced with objective AI signals.
- Capital can be rotated systematically into outperforming sectors.
- Positions can be exited efficiently as momentum fades.
This is quant-grade crypto trading — delivered directly to everyday traders.
In 2025, smart crypto traders are no longer trading charts. They’re trading AI grades.
Conclusion
As the cryptocurrency trading industry matures, traders increasingly seek smarter, data-driven solutions that remove emotion, improve timing, and boost profitability. Token Metrics’ Real-Time AI Grades are delivering exactly that.
By combining real-time price action, on-chain analytics, volatility measures, liquidity flows, and machine learning models, Token Metrics has built one of the most advanced AI crypto trading platforms available today.
If you want to succeed in cryptocurrency trading — and stay ahead of fast-moving markets in 2025 — real-time AI grading is no longer optional. It’s the new standard.
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Token Metrics Media LLC is a regular publication of information, analysis, and commentary focused especially on blockchain technology and business, cryptocurrency, blockchain-based tokens, market trends, and trading strategies.
Token Metrics Media LLC does not provide individually tailored investment advice and does not take a subscriber’s or anyone’s personal circumstances into consideration when discussing investments; nor is Token Metrics Advisers LLC registered as an investment adviser or broker-dealer in any jurisdiction.
Information contained herein is not an offer or solicitation to buy, hold, or sell any security. The Token Metrics team has advised and invested in many blockchain companies. A complete list of their advisory roles and current holdings can be viewed here: https://tokenmetrics.com/disclosures.html/
Token Metrics Media LLC relies on information from various sources believed to be reliable, including clients and third parties, but cannot guarantee the accuracy and completeness of that information. Additionally, Token Metrics Media LLC does not provide tax advice, and investors are encouraged to consult with their personal tax advisors.
All investing involves risk, including the possible loss of money you invest, and past performance does not guarantee future performance. Ratings and price predictions are provided for informational and illustrative purposes, and may not reflect actual future performance.