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Stop Guessing, Start Trading: The Token Metrics API Advantage

Announcements

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:

  1. Sign up at www.tokenmetrics.com/api
  2. Generate an API key and explore sample requests.
  3. Choose a tier–start with 50 free API calls/month, or stake TMAI tokens for premium access.
  4. 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.

Research

Understanding APIs: How They Work and Why They Matter

Token Metrics Team
5
MIN

APIs are the invisible glue that connects software, data, and services. Whether you use a weather widget, log into an app with a social account, or power AI agents with external data, APIs make those interactions possible. This guide explains what an API is, how it works, common types, and practical steps to evaluate and use them effectively.

What an API Is — Core Concept

An API (Application Programming Interface) is a set of rules and definitions that lets one software program communicate with another. At a conceptual level, an API defines the inputs, outputs, and behavior expected when you request a resource or action from a service. It abstracts implementation details so developers can use functionality without needing to understand the underlying code.

Key elements:

  • Endpoints: URLs or addresses that expose resources or actions.
  • Requests & Responses: Clients send requests (often HTTP) and receive responses, typically in JSON or XML.
  • Methods/Verbs: Common operations (e.g., GET, POST, PUT, DELETE) indicate intent.
  • Contracts: Documentation specifies parameters, data formats, and error codes.

How APIs Work — Technical Overview

Most modern APIs use web protocols. RESTful APIs use standard HTTP methods and resource-oriented URLs. GraphQL exposes a single endpoint that accepts queries describing exactly what data the client needs. WebSockets and streaming APIs enable persistent connections for real-time updates, and webhooks allow services to push events to registered endpoints.

Practical components developers encounter:

  • Authentication: API keys, OAuth tokens, JWTs, and mutual TLS verify identity and scope access.
  • Rate limits: Protect providers by limiting request frequency; plan for retries and backoff.
  • Versioning: Maintain backward compatibility by versioning endpoints.
  • Schemas: OpenAPI/Swagger and GraphQL schemas document shapes and types to reduce integration friction.

Common API Use Cases and Patterns

APIs power a wide range of applications across industries. Typical use cases include:

  • Data aggregation: Combining price feeds, social metrics, or on-chain data from multiple providers.
  • Microservices: Breaking systems into modular services that communicate over APIs for scalability and maintainability.
  • Third-party integrations: Payments, identity providers, analytics, and cloud services expose APIs for developers to extend functionality.
  • AI and agents: Models use APIs to fetch external context, perform lookups, or execute actions when building intelligent applications.

Evaluating and Using an API — Practical Checklist

Choosing or integrating an API involves technical and operational considerations. Use this checklist when researching options:

  1. Documentation quality: Clear examples, error codes, SDKs, and interactive docs accelerate adoption.
  2. Latency & reliability: Test response times and uptime; review SLAs where applicable.
  3. Security & compliance: Inspect authentication schemes, encryption, data retention, and regulatory controls.
  4. Costs & limits: Understand free tiers, metering, and rate limits to model consumption and budget.
  5. Error handling: Standardized error responses and retry guidance reduce integration surprises.
  6. SDKs and tooling: Official libraries, Postman collections, and CLI tools shorten development cycles.

When testing an API, start with a sandbox or staging environment, use automated tests for core flows, and instrument monitoring for production use. For AI projects, prioritize APIs that offer consistent schemas and low-latency access to keep pipelines robust.

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 an API?

Q: What is the difference between an API and a library?

A library is a collection of code you include in your project; an API describes interaction rules exposed by a service. Libraries run in-process, while APIs often operate over a network and imply a contract between client and provider.

FAQ: REST vs GraphQL — which to use?

REST is simple and cache-friendly for resource-oriented designs. GraphQL is useful when clients need flexible queries that reduce over- or under-fetching. The choice depends on payload patterns, caching needs, and team expertise.

FAQ: How do API keys and OAuth differ?

API keys are simple tokens tied to an account and scope; OAuth provides delegated access, user consent flows, and finer-grained permissions. For user-authorized actions, OAuth is typically preferable.

FAQ: Are public APIs secure?

Security depends on provider implementation. Public APIs can be secure when they enforce authentication, use HTTPS, validate inputs, and apply rate limiting. Always follow security best practices and assume any external interface could be targeted.

FAQ: Can APIs be used for real-time data?

Yes. Streaming APIs, WebSockets, server-sent events, and publish/subscribe webhooks deliver real-time data. Evaluate connection limits, reconnection logic, and message ordering guarantees for production systems.

FAQ: What is an SDK and why use one?

An SDK (Software Development Kit) wraps API calls in language-specific code, handling authentication, retries, and serialization. SDKs speed integration and reduce boilerplate, but it's still useful to understand raw API behavior.

Disclaimer

This article is for educational and informational purposes only. It does not constitute legal, financial, investment, or professional advice. Evaluate APIs and tools independently and consult appropriate professionals for specific use cases.

Research

APIs Explained: How Application Programming Interfaces Work

Token Metrics Team
5
MIN

APIs are the invisible glue that connects modern software: they let apps talk to services, fetch data, and automate workflows. Understanding what an API is and how it operates helps developers, analysts, and product teams design integrations that are robust, secure, and scalable.

What is an API? Definition, scope, and common types

An API, or application programming interface, is a defined set of rules and contracts that allow one software component to interact with another. At a basic level an API specifies the inputs (requests), outputs (responses), and the behavior expected when an operation is invoked. APIs can be exposed within a single application, between services inside a private network, or publicly for third-party developers.

Common API types include:

  • Web APIs (HTTP/HTTPS based, using REST or GraphQL) for browser, server, and mobile communication.
  • RPC and gRPC for high-performance binary communication between microservices.
  • Library or SDK APIs that surface methods within a language runtime.
  • Hardware APIs that expose device functionalities (e.g., sensors, GPU).
  • On-chain and crypto APIs that provide blockchain data, transaction broadcasting, and wallet interactions.

How APIs work: requests, endpoints, and protocols

APIs typically operate over a transport protocol with defined endpoints and methods. In HTTP-based APIs a client sends a request to an endpoint (URL) using methods like GET, POST, PUT, DELETE. The server processes that request and returns a response, often encoded as JSON or XML.

Key components to understand:

  • Endpoint: A specific URL or route that exposes a resource or operation.
  • Method: The action type (read, create, update, delete).
  • Schema / Contract: The shape of request and response payloads, headers, and status codes.
  • Authentication: How the API verifies the caller (API keys, OAuth tokens, signed requests).
  • Rate limits: Rules that prevent abuse by limiting request volume.

Protocols and styles (REST, GraphQL, gRPC) trade off simplicity, flexibility, and performance. REST emphasizes resource-based URLs and uniform verbs. GraphQL offers flexible queries from a single endpoint. gRPC uses binary protocols for lower latency and stronger typing.

Use cases and real-world examples (web, mobile, crypto, AI)

APIs appear in nearly every digital product. Typical use cases include:

  • Web & Mobile Apps: Fetching user profiles, submitting forms, or streaming media from cloud services.
  • Third-party Integrations: Payment providers, identity, and analytics platforms expose APIs to connect services.
  • Crypto & Blockchain: Nodes, indexers, and market data providers expose APIs to read chain state, broadcast transactions, or retrieve price feeds.
  • AI & Data Pipelines: Models and data services expose inference endpoints and training data APIs to enable programmatic access.

For analysts and product teams, APIs make it possible to automate data collection and combine signals from multiple services. AI-driven research tools such as Token Metrics rely on API feeds to aggregate prices, on-chain metrics, and model outputs so users can build informed analytics workflows.

Design, security, and operational best practices

Well-designed APIs are predictable, versioned, and documented. Consider these practical guidelines:

  1. Design for clarity: Use consistent naming, predictable status codes, and clear error messages.
  2. Versioning: Provide v1/v2 in paths or headers so breaking changes don’t disrupt clients.
  3. Rate limiting and quotas: Protect backend resources and provide transparent limits.
  4. Authentication & Authorization: Use proven schemes (OAuth2, signed tokens) and enforce least privilege.
  5. Input validation and sanitization: Defend against injection and malformed payloads.
  6. Observability: Implement logging, metrics, and distributed tracing to monitor performance and troubleshoot failures.
  7. Documentation and SDKs: Publish clear docs, example requests, and client libraries to reduce integration friction.

Security in particular requires ongoing attention: rotate credentials, monitor for anomalous traffic, and apply patching for underlying platforms. For teams building systems that depend on multiple external APIs, plan for retries, exponential backoff, and graceful degradation when a provider is slow or unavailable.

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 an API?

Q1: What is the difference between an API and an SDK?

An API is a contract that defines how to interact with a service. An SDK is a packaged set of tools, libraries, and helpers that implement or wrap that API for a specific language or platform.

How do REST and GraphQL differ?

REST uses multiple endpoints and standard HTTP verbs to model resources; GraphQL exposes a single endpoint where clients request exactly the fields they need. REST is simpler; GraphQL can reduce over-fetching but adds query complexity.

Can APIs return real-time data?

Yes. Real-time patterns include WebSockets, server-sent events, or streaming gRPC. Polling a REST endpoint is simpler but less efficient for high-frequency updates.

What are common API security measures?

Common measures include strong authentication (OAuth2, API keys), TLS encryption, rate limiting, input validation, signed requests, and robust monitoring for abuse or anomalies.

How should teams evaluate third-party APIs?

Assess uptime history, SLAs, documentation quality, rate limits, pricing model, security posture, and whether the API provides the required schemas and latency characteristics for your use case.

Can APIs be used with AI applications?

Yes. AI models often expose inference APIs for serving predictions, and research tools consume multiple APIs to aggregate training data, features, or market signals. Designing for reproducibility and input validation is important when feeding models with API-derived data.

Disclaimer

This article is educational and informational in nature. It does not provide investment, legal, or professional advice. Implementations and integrations described here are technical examples and should be validated in your environment before deployment.

Research

Understanding APIs: A Practical Guide

Token Metrics Team
6
MIN

APIs power modern software by letting systems communicate without sharing internal code. Whether you use a weather app, social login, or an AI assistant, APIs are the invisible glue connecting services. This guide explains what an API is, how APIs work, practical use cases (including crypto and AI), and criteria to evaluate an API for research or product use.

What is an API? A clear definition

API stands for Application Programming Interface. At its simplest, an API is a set of rules and protocols that lets one program request services or data from another. Think of an API as a restaurant menu: the menu lists dishes (endpoints) you can order (requests), the kitchen prepares the dish (service), and the waiter delivers it to your table (response). The consumer of the API doesn’t see how the kitchen is organized; it only needs to know how to order.

APIs abstract complexity, standardize interactions, and enable modular design. They exist at many layers — from operating systems and libraries to web services that return JSON or XML. For developers and researchers, APIs are indispensable for integrating external data, automating workflows, and composing distributed systems.

How APIs work: architecture, formats, and types

Most modern web APIs follow request/response patterns over HTTP. Key concepts include:

  • Endpoints: URL paths that expose specific resources or actions, e.g., /prices or /users.
  • Methods: HTTP verbs like GET (retrieve), POST (create), PUT/PATCH (update), DELETE (remove).
  • Payloads: Data sent or received, often formatted as JSON for web APIs.
  • Authentication: API keys, OAuth tokens, or signed requests to control access.

Architectural styles and protocols include REST (resource-oriented, stateless), GraphQL (client-specified queries), gRPC (binary, streaming), and WebSockets (persistent full-duplex connections). Each has trade-offs: REST is simple and cache-friendly; GraphQL reduces over-fetching but can complicate caching; gRPC excels in performance for internal microservices.

APIs in crypto and AI: data, execution, and agents

In crypto and AI ecosystems, APIs serve several roles:

  • Market data APIs: Provide price feeds, order book snapshots, historical candles, and index data used for analysis and visualization.
  • Blockchain & on-chain APIs: Expose transaction data, smart contract interactions, wallet balances, and event logs for on-chain analysis.
  • Execution/trading APIs: Let platforms submit orders, query trade status, and manage accounts. These require strict auth and latency considerations.
  • AI & model APIs: Offer inference services, embeddings, or model orchestration endpoints for tasks like NLP, classification, or agent behavior.

Combining these APIs enables product capabilities such as automated research pipelines, AI agents that react to market signals, and dashboards that mix on-chain metrics with model-driven insights. Many teams use dedicated crypto APIs to aggregate exchange and chain data, and AI-driven tools to surface patterns without exposing trading recommendations.

For example, researchers might ingest price and on-chain feeds through a market API, compute custom signals with an AI model, and expose those signals via an internal API for front-end consumption. When evaluating providers, consider freshness of data, coverage across assets/chains, and documented latency characteristics.

How to evaluate, integrate, and maintain APIs

Choosing and integrating an API is not just about endpoints. Use a checklist that covers technical, operational, and governance concerns:

  1. Documentation quality: Look for clear examples, error codes, and sandbox endpoints for testing.
  2. Authentication and security: Prefer APIs that support scoped keys, granular permissions, and strong transport security (TLS).
  3. Rate limits & pricing: Understand request quotas, burst limits, and throttling behavior to design backoff strategies.
  4. Data guarantees: Check latency, update frequency, historical depth, and whether data is normalized across sources.
  5. SLA and reliability: Uptime history, status pages, and support SLAs matter for production use.
  6. Monitoring & observability: Log requests, track error rates, and monitor latency to detect regressions or abuse.

Integration tips: start with a sandbox key, write thin adapters to isolate provider-specific formats, and implement exponential backoff with jitter for retries. For analytics workflows, cache immutable historical responses and only refresh dynamic endpoints when necessary.

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: common questions about APIs

What is the difference between REST and GraphQL?

REST exposes resources through fixed endpoints and relies on HTTP methods. GraphQL lets clients specify exactly what fields they need in a single query. REST is simpler and benefits from existing HTTP caching; GraphQL reduces over-fetching but can require more complex server-side tooling.

How do API keys and OAuth differ?

API keys are simple tokens issued to clients, often for server-to-server access or basic identification. OAuth is an authorization framework that issues scoped access tokens on behalf of users, enabling delegated permissions and better control over access lifecycle.

What are common API failure modes to plan for?

Rate limiting, transient network errors, schema changes, and authentication failures are typical. Design clients to retry with exponential backoff, validate responses, and fail gracefully when dependencies are degraded.

How can I secure sensitive data when using third-party APIs?

Use encrypted transport (TLS), rotate credentials regularly, scope keys to minimum permissions, and avoid embedding secrets in client-side code. For sensitive workflows, consider a server-side proxy that enforces access policies and masking.

Can AI models be accessed via APIs and how does that affect workflows?

Yes. Many AI models expose inference and embedding endpoints. Using model APIs decouples compute from your product stack, simplifies scaling, and enables A/B testing of models. Evaluate latency, cost per request, and data retention policies when choosing a provider.

How do I test and validate an API integration?

Start in a sandbox environment, create automated integration tests covering success and failure cases, mock third-party responses for unit tests, and run load tests against rate limits. Monitor post-deployment with health checks and alerts.

What are rate limits and how should clients handle them?

Rate limits cap how many requests a client can make in a time window. Clients should respect headers that indicate remaining quota, implement exponential backoff with jitter on 429 responses, and batch requests or cache results when possible.

When should I build my own API versus using a third-party API?

Use a third-party API for non-core data or services where speed-to-market and maintenance offload matter. Build an internal API when the capability is strategic, requires proprietary processing, or when you need tight control over latency, privacy, and SLAs.

How can tools like Token Metrics help with API-driven research?

Data and model platforms can centralize feeds, normalize formats, and provide analytical signals that reduce the engineering overhead of assembling multiple APIs. Token Metrics is an example of a platform that merges model-driven insights with market and on-chain data for research workflows.

Disclaimer

This content is for educational and informational purposes only. It does not constitute financial, legal, or investment advice. Evaluate APIs and services independently and consult appropriate professionals for decisions that involve risk.

Recent Posts

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Research

Solana Price Action: Will the Bulls Regain Control? Token Metrics Signals Offer Clues

Token Metrics Team
4 min
MIN

Solana has been one of the most closely watched altcoins in the 2025 crypto cycle. With its blazing speed, developer activity, and expanding DePIN ecosystem, Solana has remained on every smart investor’s radar. But with the broader market pulling back sharply — and Bitcoin dipping below $105K — traders are asking: Is Solana still a buy?

Token Metrics' AI-powered tools offer critical insights into this volatile moment.

April's Bullish Signal Paid Off
Token Metrics’ proprietary indicator turned bullish on Solana on April 19, when the price was just $138.18. That signal wasn’t just noise. Within a month, Solana surged by 33.1%, reaching $184 by May 23.

This kind of real-time, data-driven signal is exactly why traders are turning to Token Metrics. Rather than guessing or chasing hype, our platform delivers objective, AI-backed alerts that help traders enter early and exit intelligently.

The Pullback: Market-Wide, Not Solana-Specific
Fast forward to today, and the story has changed. Solana is undergoing a major pullback, largely driven by the overall market correction. Bitcoin’s slide below $105K has dragged most altcoins down, Solana included.

However, Token Metrics' Trader Grade for Solana is now 'Neutral' — not bearish. That’s a crucial distinction. While momentum has cooled, our system is not yet signaling a full reversal. That means there’s still room for recovery.

Technical Outlook: The $160 Level is Critical
Technical analysis highlights a key battleground at $160. If bulls can reclaim this level in the near term, the uptrend could resume. Failure to hold above it, however, could open the door for deeper losses.

Token Metrics users can monitor these levels in real-time with our dynamic charts, trend indicators, and updated market signals.

What Traders Should Watch Next

  • Market Signal Shift: If the Token Metrics market signal flips to bearish, it’s a red flag. Until then, volatility may still offer upside.
  • $160 Breakout: This is the technical threshold bulls must defend.
  • Volume and Sentiment: A spike in volume or positive narrative news could signal a reversal.

Conclusion
Solana remains a high-potential asset — but trading it without real-time analytics in this environment is risky. Token Metrics doesn’t just tell you what’s happening; it shows why it’s happening and what to do next.

Join Token Metrics today to access AI-powered trading signals, risk analysis, and the tools to trade crypto like a pro — even in uncertain markets.

Research

Bearish Signals Ahead? How to Spot Early Warnings Before a Crash

Token Metrics Team
4 min
MIN

In crypto, everything can change overnight. One minute the market’s bullish — the next, it’s bleeding red. That’s why the ability to spot bearish signals early is crucial for protecting capital and maximizing long-term gains. Token Metrics gives traders an edge with AI-driven alerts that help you act before the crash hits.

Why Most Traders Miss the Top
Retail traders often get caught in the hype. By the time “everyone” is talking about a token, it’s usually too late. The smartest investors are watching subtle changes in data: volume drops, negative sentiment, weakening momentum.

Token Metrics makes those patterns visible before price crashes.

What Is a Bearish Signal on Token Metrics?
A bearish signal is a warning based on:

  • Declining Trader Grade (below 30)
  • Negative ROI since signal
  • Volume drying up while price holds
  • Bearish crossover in trend indicators
  • Weakening fundamentals or fading narratives

These signals are automatically triggered and displayed on the Market Page.

How to Identify Bearish Tokens Early

  1. Sort by Negative ROI – See which tokens have declined most after a bold signal.
  2. Filter by Trader Grade < 30 – These are tokens losing short-term momentum.
  3. Look for Divergence – If price is flat but volume or sentiment drops, the setup may be turning bearish.

Behavioral Clues You Shouldn’t Ignore

  • Signal stops updating – Token Metrics halts signals when confidence fades.
  • Narrative dies down – No more tweets, community quiets down? Trouble ahead.
  • Trending to Stagnant – Tokens drop from Top Gainers list quickly.

Real Example: Avoiding Losses with Signal Data
Ian Balina mentioned how users avoided major losses by exiting weak tokens early thanks to falling grades and bearish signals. Instead of hoping, they acted — preserving capital and rotating into stronger plays like Launch Coin or AI tokens.

What to Do When You See Bearish Signs

  • Don’t panic – Act on data, not emotion.
  • Set stop-losses based on bold signal entry points.
  • Rotate capital into high-grade tokens or stablecoins.
  • Monitor daily – The market can flip from bullish to bearish in hours.

Combining Risk Management with Signals
Token Metrics isn’t just about finding moonshots. It’s also about knowing when not to buy or when to exit early. By using bearish signals, you protect yourself from downside while staying positioned for the next big opportunity.

Conclusion
The best crypto traders aren’t just profit-hunters — they’re risk managers. Bearish signals from Token Metrics help you anticipate weakness, reduce losses, and trade with clarity. In a volatile market, that edge can make all the difference.

Research

From Retail to Institutions: Who’s Driving the Crypto Market in 2025?

Token Metrics Team
4 min
MIN

Crypto markets are evolving — and fast. In the early days, retail investors dominated the space. But by 2025, the tides are shifting. Institutional investors, family offices, and algorithmic funds are entering the market at scale. This blog explores the growing divide — and how it’s reshaping opportunities for everyday traders.

The Rise of Institutional Money in Crypto
Over the last year, a new class of investors has emerged: professional firms with deep pockets and long-term horizons. They're no longer just “exploring crypto” — they’re actively deploying capital.

Why now?

  • Regulatory clarity in major jurisdictions
  • Bitcoin ETF approvals and crypto fund launches
  • Better custody, risk management, and analytics tools (including Token Metrics)

What Are Institutions Buying?
Institutions tend to avoid meme coins and hyper-volatility. Instead, they focus on:

  • Layer 1 Infrastructure – Ethereum alternatives like Sui and Avalanche
  • AI Tokens – Leveraging real-world utility and strong narratives
  • DeFi Blue Chips – Projects with consistent TVL and governance upgrades
  • Stable Yield Strategies – On-chain bonds, staking, and real-world asset tokens

Token Metrics has seen a spike in institutional users filtering by Investor Grade and project fundamentals.

Retail Traders Still Dominate One Arena
Retail traders are far from out — they dominate high-volatility narratives:

  • Meme tokens
  • Social coin launches (e.g., Launchcoin)
  • Short-term speculation based on influencer sentiment

Retail’s edge? Speed, risk tolerance, and virality. Many of Token Metrics’ bold signals still originate from this activity before institutions catch on.

Token Metrics Bridging the Divide
What makes Token Metrics powerful in 2025 is its ability to serve both segments:

  • Institutions use it for due diligence, grades, and long-term planning.
  • Retail traders use it for short-term signals, alerts, and narrative tracking.

This dual capability creates a level playing field, where data, not capital, is the edge.

How to Trade Based on Who’s in Control

  1. When institutions lead – expect slower but more sustainable growth. Focus on high Investor Grade tokens.
  2. When retail leads – expect fast-moving pumps and dumps. Use high Trader Grade + bold signals.
  3. Hybrid phase (now) – Use both metrics to balance volatility and long-term conviction.

Market Behavior Patterns to Watch

  • Low volatility + high inflows → Institutional buildup
  • High volume + sudden spikes → Retail-driven narratives
  • Diverging BTC vs. altcoin trends → Mixed sentiment cycles

Conclusion
The crypto market in 2025 is being driven by both the old guard and the new wave. Institutions bring maturity. Retail brings momentum. Smart investors use tools like Token Metrics to read the room — and position themselves accordingly.

Research

Trader vs. Investor Grade: How to Use Both for Smarter Crypto Bets

Token Metrics Team
4 min
MIN

Crypto trading success often boils down to timing. But how do you know when to enter — and when to stay long? Token Metrics solves this dilemma with a dual-grade system: Trader Grade and Investor Grade. Each grade serves a different investment goal, and together, they help you make more confident decisions, whether you’re day trading or holding for the long run.

What is the Trader Grade?
The Trader Grade measures short-term momentum. It uses AI to analyze price action, volume trends, technical indicators, and recent sentiment shifts. Scores range from 0 to 100, and a score above 80 signals strong short-term potential.

Use Case:

  • Perfect for swing traders and short-term opportunists.
  • Look for tokens with Trader Grade > 80 for potential breakout trades.
  • Example: Launchcoin had a Trader Grade above 90 before its 35x rally began.

What is the Investor Grade?
The Investor Grade focuses on long-term fundamentals. It’s designed for those who want to hold tokens for months or even years. This grade considers tokenomics, development activity, ecosystem strength, narrative alignment, and long-term price structure.

Use Case:

  • Ideal for long-term portfolio builders.
  • A token with Investor Grade > 80 is a strong candidate for accumulation.
  • AI infrastructure tokens and modular blockchains often rank high here.

Why Use Both?
Most traders fail by only looking at hype or short-term charts. Token Metrics lets you blend data:

  • High Trader Grade + Low Investor Grade? Consider a short-term trade, not a long hold.
  • High Investor Grade + Low Trader Grade? Consider waiting for a better entry point.
  • Both High? Green light for confidence in both entry and long-term performance.

Case Study: Balancing Your Portfolio with Grades
Users can use the dual-grade approach for smarter allocation:

  • 30% of capital to high Trader Grade tokens (short-term plays)
  • 70% to high Investor Grade tokens (long-term holds)

This method helps mitigate risk and improve overall ROI.

Where to Find the Grades
Both grades are displayed prominently across:

  • Token Detail Pages – Real-time grade updates with historical data
  • Market Page Filters – Sort tokens by grade thresholds
  • Portfolio Builder Tool – Automatically selects tokens with strong grades

Tips for Grade-Based Trading

  1. Use Trader Grade for volatile markets or when prices are accelerating.
  2. Use Investor Grade when building positions in strong narratives like AI, DeFi, or infrastructure.
  3. Avoid tokens with both grades below 60 unless you’re making a speculative bet.

Conclusion
Trading without context is gambling. Token Metrics’ Trader and Investor Grades give you a proven framework for assessing both momentum and fundamentals. Whether you’re here for a quick flip or a long-term bet, using the dual-grade system can level up your crypto strategy.

Announcements

Inside the Dashboard: How to Monitor API Key Activity and Monthly Usage in Real Time

Token Metrics Team
5 min
MIN

The power of any great API isn’t just in the data it provides — it’s also in the control, visibility, and accountability it gives developers. That’s why the Token Metrics API Dashboard is more than just a place to generate keys — it’s your real-time command center for monitoring API key usage, managing access, and optimizing performance.

In this article, we’ll explore how to use the Token Metrics API Dashboard to stay in control of your app’s data usage, track request history, and ensure your integrations remain secure and efficient.

📍 Where to Find It

To access the dashboard:

  1. Log in to your Token Metrics account.
  2. Go to: https://app.tokenmetrics.com/en/api
  3. Navigate to the API Keys and API Usage sections.

🔐 View and Manage API Keys

The API Keys section gives you a complete overview of every active key associated with your account. For each key, you’ll see:

  • Key Name: Descriptive labels like "Bot A" or "Staging Server"
  • Created Date: When the key was generated
  • Last Used: Timestamp of the most recent request
  • Status: Active or inactive toggle
  • Actions: Trash icon to instantly delete a key

💡 Why It Matters:

  • Spot unused or stale keys that may pose a security risk
  • Instantly disable or delete a key if it’s compromised
  • Monitor which app or environment is making the most requests

📊 Monitor API Usage in Real-Time

In the Usage Dashboard, Token Metrics gives you deep insights into how your API credits are being used.

Key metrics include:

  • API Calls Graph
    A daily call volume chart so you can identify peaks in usage, anomalies, or unexpected surges.

  • Total Monthly API Calls
    Example:
    8,750 / 20,000
    See how much of your monthly quota you’ve used — and when it resets.

  • Remaining API Credits
    Know exactly how many calls you have left in your current cycle.

  • API Call Statistics Table
    Each row includes:

    • Endpoint accessed (e.g., /trader-grade)
    • Timestamp of the request
    • Status code (200 = success, 401 = unauthorized, etc.)
    • Originating IP address
    • Success/failure response

🔄 Debugging & Insights Made Easy

This dashboard doesn’t just monitor—it helps you debug and optimize.

  • Quickly identify if your integration is repeatedly hitting 400 or 403 errors
  • Check whether a specific key is being overused or underused
  • Pinpoint spikes in usage that may indicate unauthorized access
  • See which endpoints are called most often — and consider caching results

⚠️ Avoid Rate Limit Surprises

If you’re on a Basic or Advanced plan, you’ll have a rate limit (e.g., 1 req/min for free users, up to 600 req/min for VIPs). The dashboard helps ensure you stay within your limits — and scale appropriately when needed.

🚀 Build Better with Transparency

In a production environment, visibility into API activity is critical. With Token Metrics, you’re never flying blind. You always know:

  • Which app is using which key
  • How many credits you’re using
  • When to optimize or upgrade

From security to scaling, the Token Metrics API Dashboard gives you the insight you need to build with clarity and control.

👉 Launch Your API Dashboard Now → tokenmetrics.com/api

Research

Is the Crypto Market Bullish or Bearish? Why 2025 Is the Year of Neutral Momentum

Token Metrics Team
3 min
MIN

The crypto market isn't clearly bullish or bearish in mid-2025 — it's neutral. This article explores why this 'in-between' momentum could signal a maturing market cycle, and what investors should watch for as signals normalize after a sharp $1T rebound in total market cap.

As we navigate through the midpoint of 2025, one question dominates trading desks and Telegram groups alike: Is the crypto market bullish or bearish? Surprisingly, the answer might be neither. Current indicators suggest that we are in a neutral zone — an ambiguous space where the market is no longer surging with euphoric gains but isn’t plunging into panic either.

From January through mid-May, the total crypto market cap has grown from $1 trillion to $2 trillion. This swift rebound signals recovery, but not full-blown optimism. Instead, many analysts — ourselves included — interpret this as a healthy correction and stabilization following intense early-year volatility.

This kind of environment often marks the early stages of a maturing cycle. Unlike the sharp swings we saw in previous bull and bear markets, 2025’s trend suggests more measured growth, driven by fundamentals rather than hype. In other words, the market might finally be learning from its past.

That doesn’t mean the space lacks activity. Sectors like DeFi lending and AI-related tokens continue to gain traction, with significant TVL inflows. Retail interest in meme coins also remains high in select regions. But overall, what we’re seeing is consolidation — not chaos.

In this neutral setting, strategy matters more than sentiment. It's no longer about jumping into trending narratives or panic-selling on dips. Instead, identifying projects with real use cases, sustainable economics, and strong communities has become the foundation of long-term success.

For traders and builders alike, the current landscape offers both challenges and opportunities. Risk-adjusted returns are key, and disciplined portfolio rebalancing could be one of the most underrated strategies right now.

As we continue monitoring market signals, we remain committed to surfacing actionable insights backed by real-time data, not just narratives. Whether the next breakout is weeks or months away, staying informed — and unemotional — may prove to be your best edge.

How Token Metrics Helps in a Neutral Market Environment:

In times of neutral momentum, making profitable crypto decisions becomes more complex — and that's where Token Metrics shines:

  1. Actionable AI Signals:
    Token Metrics scans thousands of tokens daily, using over 80 data points to identify bullish and bearish trends even when market sentiment is flat. This helps users cut through noise and act on real opportunities.
  2. Investor & Trader Grades:
    When hype fades, fundamentals matter. Our proprietary grades evaluate both short-term momentum and long-term viability, helping users discover tokens with staying power — not just temporary pumps.
  3. Smart Rebalancing Alerts:
    In a consolidating market, maintaining the right portfolio mix is crucial. Token Metrics' indices and alerts help users rebalance regularly to lock in gains and minimize downside risks.
  4. Sector-Based Insights:
    With DeFi, AI, and meme coins behaving differently, Token Metrics allows users to dive deep into sector-specific analytics — so you can position ahead of capital flows.
  5. Sentiment & Volume Monitoring:
    Our platform tracks shifts in on-chain activity, social sentiment, and volume trends to spot early signs of market reversals — especially useful when traditional signals stall.

In a market where being early beats being emotional, Token Metrics equips you with the clarity and tools to trade with confidence.

Announcements

🚀 Announcing the Launch of the Token Metrics API & SDK — Powered by $TMAI

Token Metrics Team
5 min
MIN

Introducing the Token Metrics API: Power Your Crypto Tools with AI-Driven Intelligence

We’re thrilled to announce one of our most important product launches to date: the Token Metrics API is now live.

This powerful crypto API gives developers, quant traders, and crypto startups direct access to the core AI infrastructure that powers the Token Metrics platform. Whether you’re building trading agents, investor dashboards, research tools, or mobile apps, our API and SDKs provide everything you need to build with real-time crypto data and intelligence—right out of the box.

For the first time, you can plug into the same AI API that drives our ratings, signals, and predictions—and embed it directly into your products, tools, or internal systems.

🔍 What’s Inside the Token Metrics API?

Our crypto API is designed to give you high-performance access to the exact data models we use in-house:

✅ AI Trading Signals

Access bullish and bearish calls across thousands of tokens. These API endpoints are powered by machine learning models trained on historical price action, sentiment data, and blockchain activity.

✅ Investor & Trader Grades

Through our API, you can pull dynamic 0–100 grades on any token. Designed for long-term or short-term views, these scores factor in volatility, momentum, market cap trends, and our proprietary AI predictions.

✅ AI Reports & Conversation Crypto Agent

Query the API to generate custom reports and insights using our smart crypto assistant. Analyze market trends, token health, and investment opportunities—without writing your own models.

✅ Token Performance Data

Retrieve token-level analytics like ROI, predictive volatility, and asset rankings. Perfect for powering dashboards, investor tools, or internal models.

✅ Market Sentiment Models

Use the API to access our AI-modeled sentiment engine, built from social media, news data, and trend signals—ideal for gauging crowd psychology.

All Token Metrics API endpoints are RESTful, fast, and easy to integrate. SDKs for Python, Node.js, and other environments help developers onboard quickly.

🛠️ What You Can Build With the Token Metrics API

Our users are already building next-gen tools and automation using the Token Metrics API:

  • 🤖 CEX Trading Agents — Automate entries and exits with real-time signals and token grades
  • ⛓️ DEX Arbitrage Engines — Scan price differences across DeFi and act instantly
  • 📊 Analytics Dashboards — Build data-driven tools with predictive metrics and visualizations
  • 💬 Alert Bots for Telegram & Discord — Deliver actionable alerts using our signal API
  • 📱 Web & Mobile Crypto Apps — Enhance portfolios and research apps with AI intelligence

With just a few lines of code and an API key, you can turn static crypto apps into dynamic, intelligent systems.

💸 Affordable Pricing & $TMAI Utility

We’ve designed our crypto API pricing to be flexible and accessible:

  • Plans start at $99/month, with high usage limits
  • Save up to 35% when you pay with our native token, $TMAI
  • All tiers include access to powerful AI tools and real-time crypto data

Whether you're a solo dev or scaling a trading startup, there’s a plan built for you. Paying with $TMAI also deepens your utility in the Token Metrics ecosystem—this is just the beginning of native token perks.

🧪 Try the Token Metrics API for Free

Not ready to commit? Try our free API tier with:

  • Limited endpoints to explore
  • Access to live documentation and test queries
  • Sample code and SDKs for instant implementation

Start exploring at tokenmetrics.com/api

🌐 Why We Built This Crypto API

Token Metrics has always been focused on empowering smarter investing. But as the market evolves, we believe the future lies in infrastructure, automation, and open access.

That’s why we built the Token Metrics API—to give developers access to the exact AI systems we use ourselves. Our models have been fine-tuned over years, and now, that same intelligence can power your platform, tools, or trading agents.

Whether you're building research platforms, signal-based apps, or automated execution tools—this API is your edge.

⚡ Start Building with Token Metrics API for FREE→ tokenmetrics.com/api

The crypto market never sleeps—and with the Token Metrics API, neither do your tools.

Research

Inside Token Metrics’ Market Page Upgrade: Smarter Signal Discovery

Token Metrics Team
5 min
MIN

Introduction
With thousands of crypto tokens flooding the market, finding the best-performing assets can feel like searching for a needle in a haystack. Token Metrics is solving this with a revamped Market Page experience — designed to surface top signals faster and help users make smarter trading decisions.

Why the Market Page Matters
The Market Page is the heartbeat of Token Metrics' analytics platform. It showcases real-time data on the latest bullish and bearish signals across tokens, providing users with instant access to the platform’s top-rated opportunities. With the recent update, it’s now more powerful and user-friendly than ever.

What’s New in the Market Page?

  1. Top-Performing Signals First – The layout now prioritizes tokens with the highest ROI bold signals. This means the most alpha-generating opportunities are surfaced first — saving users valuable time.
  2. Smarter Filters – Users can sort by return, grade, time frame, and signal type. Want only tokens with a Trader Grade above 80? Just one click away.
  3. Improved Visuals – A cleaner UI now highlights key metrics like entry price, ROI since signal, and latest update date.

How It Helps Traders
This upgrade isn't just cosmetic. It fundamentally changes how traders interact with the platform:

  • Faster decision-making by highlighting the best signals up front
  • Better precision using advanced filters for investor profiles
  • Increased confidence from seeing clear data behind every signal

Case Study: Launch Coin
Launch Coin, the best performing token in 2025 with a 35x return, was identified early thanks to the Market Page’s bold signal tracking. Its signal rose to the top immediately after performance started climbing — helping early users lock in life-changing gains.

How to Use the Market Page Like a Pro

  1. Visit the Market Page daily to track new signal updates
  2. Filter by 24H/7D ROI to catch fast movers
  3. Use Grades to Align with Your Strategy
  4. Follow Narratives: Filter by AI, DeFi, Gaming, and other emerging themes

The Power of Daily Signals
With market conditions changing fast, the daily updates on the Market Page give Token Metrics users an edge — surfacing fresh opportunities before they trend on social media or make headlines.

Conclusion
The new Market Page isn’t just a dashboard — it’s a discovery engine. Designed for both beginner and experienced traders, it brings clarity, speed, and precision to crypto investing.

Research

Bitcoin vs. Altcoin Season: Where the Market's Headed in 2025

Token Metrics Team
5 min
MIN

Introduction
In the ever-evolving world of crypto, understanding the cyclical relationship between Bitcoin and altcoins is crucial for successful trading. During Token Metrics’ latest market update, Ian Balina highlighted key indicators pointing to a shift in momentum — possibly signaling the return of an altcoin season.

What Is Altcoin Season?
Altcoin season is a period in the crypto market where altcoins outperform Bitcoin in terms of price gains. Historically, this shift occurs when Bitcoin stabilizes after a rally, giving room for capital rotation into smaller-cap tokens with higher risk/reward potential.

Bitcoin’s Dominance and the Signs of Rotation
As of May 2025, Bitcoin remains a market anchor, but its dominance is showing signs of plateauing. Ian pointed out that capital is beginning to flow into AI tokens, new infrastructure plays, and community-driven projects like Launchcoin — which has already returned 35x gains. These trends are classic precursors to altcoin season.

Top Performing Altcoins Identified by Token Metrics
Token Metrics’ bold signals have identified several high-performing altcoins, such as:

  • Launchcoin: 35x gain since the signal triggered.
  • AI Infrastructure Tokens: Benefiting from the broader AI narrative in crypto.
  • DeFi 2.0 Protocols: Getting renewed attention amid institutional interest.

Key Indicators to Watch

  1. Bitcoin Dominance Chart – A drop below 50% dominance often precedes altcoin rallies.
  2. Volume Trends – Increasing volume on altcoin pairs indicates rising interest.
  3. Token Metrics Grades – Look for altcoins with high Trader and Investor Grades — a dual signal of short- and long-term strength.

How to Prepare Your Portfolio
Traders should consider gradual rotation — locking in BTC gains and reallocating to top-rated altcoins. Using Token Metrics’ tools:

  • Monitor daily signal updates
  • Filter by Trader Grade > 80 and recent bold signals
  • Keep an eye on AI and DeFi narratives, as they dominate 2025’s momentum

Conclusion
Whether we’re entering a full-blown altcoin season or just a mini-cycle, the signals are clear: capital is rotating. Use data, not guesswork. With Token Metrics’ AI-powered tools, you can identify high-potential opportunities and stay ahead of the curve in both Bitcoin and altcoin markets.

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