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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

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.

Research

APIs Explained: How They Power Apps and AI

Token Metrics Team
6
MIN

APIs are the invisible connectors that let software talk to software. Whether you book a flight, check a crypto price, or ask an AI agent to summarize a document, APIs are likely working behind the scenes. This guide breaks down what an API is, how it works, common types and use cases, and practical steps for research and integration.

What is an API?

An API, or application programming interface, is a defined set of rules and data structures that lets one software component request services or data from another. Think of an API as a contract: the provider exposes endpoints and data formats, and the consumer uses those endpoints to perform actions or retrieve information. This abstraction hides implementation details, enabling interoperability and composability across systems.

At its core, an API specifies:

  • Available operations (endpoints) and accepted parameters
  • Request and response formats (JSON, XML, etc.)
  • Authentication and rate limits
  • Error handling and status codes

APIs accelerate development by allowing teams to reuse services instead of rebuilding functionality. They also enable ecosystems: marketplaces, integrations, and data sharing across organizations.

How APIs Work: Components & Protocols

APIs are implemented over protocols and architectural styles. The most common is REST (Representational State Transfer), which uses HTTP verbs (GET, POST, PUT, DELETE) and URIs to model resources. Alternatives like GraphQL let clients request specific data shapes, which can reduce over- and under-fetching in complex applications.

Key components to understand:

  • Endpoint: A URL representing a resource or action (e.g., /api/v1/prices).
  • Method: The HTTP action to perform (GET to read, POST to create).
  • Payload: The body of a request for create/update operations, usually JSON.
  • Authentication: API keys, OAuth tokens, or other schemes control access.
  • Rate limits: Providers throttle requests to protect services.

Beyond REST and GraphQL, there are webhooks (server-to-server push notifications), gRPC for high-performance RPC-style communication, and socket-based APIs for real-time streams. The choice of protocol affects latency, throughput, and developer ergonomics.

Types of APIs and Real-World Use Cases

APIs come in several flavors depending on visibility and purpose:

  • Public APIs: Exposed to external developers for integrations and apps.
  • Private APIs: Internal to an organization, used to modularize services.
  • Partner APIs: Shared with selected partners under specific agreements.

Common use cases illustrate how APIs deliver value:

  • Payment processing APIs enable e-commerce sites to accept credit cards without storing sensitive data.
  • Mapping and location APIs power ride-hailing, logistics, and geofencing features.
  • Data APIs supply market prices, on-chain metrics, or social feeds for dashboards and trading bots.
  • AI and ML model APIs let applications delegate tasks like transcription, summarization, or image analysis to cloud services.

For example, crypto applications rely heavily on exchange and on-chain data APIs to aggregate prices, monitor wallets, and execute analytics at scale. Evaluating latency, historical coverage, and data quality is critical when selecting a provider for time-series or transactional data.

How Developers and AI Use APIs

Developers use APIs to compose microservices, integrate third-party functionality, and automate workflows. For AI systems, APIs are essential both to access model inference and to fetch context data that models use as inputs.

Practical patterns include:

  1. Chaining: Calling multiple APIs in sequence to enrich a response (e.g., fetch user profile, then fetch personalized recommendations).
  2. Caching: Store frequent responses to reduce latency and cost.
  3. Bulk vs. Stream: Use batch endpoints for historical backfills and streaming/webhooks for real-time events.

When integrating APIs for analytics or AI, consider data consistency, schema evolution, and error semantics. Tools and platforms can monitor usage, surface anomalies, and provide fallbacks for degraded endpoints.

For researchers and teams assessing providers, structured evaluations help: compare SLA terms, data freshness, query flexibility, cost per request, and developer experience. Platforms that combine market data with AI-driven signals can accelerate exploratory analysis; for example, Token Metrics provides AI-backed research and ratings that teams often use to prioritize datasets and hypothesis testing.

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 a library?

An API defines a set of rules and endpoints for interaction between systems, often over a network. A library is a local collection of functions and classes that an application links to at runtime. Libraries run in-process; APIs often run across processes or machines.

FAQ — How secure are APIs?

Q2: How should APIs be secured?

Common security measures include authentication (API keys, OAuth), encryption (TLS), input validation, rate limiting, and monitoring for anomalous patterns. Security practices should match the sensitivity of data and regulatory requirements.

FAQ — REST vs. GraphQL

Q3: When to choose REST over GraphQL?

REST is simple and well-suited to resource-based designs and caching. GraphQL is useful when clients need precise control over returned fields and want to minimize round trips. The right choice depends on client needs, caching strategy, and team expertise.

FAQ — What drives API costs?

Q4: What factors affect API pricing?

Pricing typically depends on request volume, data granularity, retention of historical data, and premium features such as websockets, SLAs, or enriched analytics. Evaluate costs under realistic usage patterns and spikes.

FAQ — How to get started with an API?

Q5: How do I evaluate and integrate a new API?

Start by reading docs, testing sandbox endpoints, and estimating request volumes. Validate data formats, authentication flows, and edge cases (rate limits, errors). Prototype with small workloads before committing to production usage.

FAQ — Are APIs regulated?

Q6: Do APIs involve legal or compliance considerations?

APIs that handle personal data, financial transactions, or regulated assets may be subject to privacy laws, financial regulations, or contractual obligations. Assess compliance requirements, data residency, and logging needs early in the design process.

Disclaimer

This article is for educational purposes only and does not constitute investment, legal, or professional advice. Information contained here is neutral and analytical; always perform independent research and consult qualified professionals for decisions involving legal or financial risk.

Recent Posts

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Research

📈 Launch Coin’s Wild Ride: From 54 SOL to $4 Million

Token Metrics Team
4 min
MIN

The crypto world thrives on narratives, and few have captured attention in recent weeks like Launchcoin. Born from a blend of SocialFi innovation and meme-driven virality, Launchcoin has surged into the spotlight—offering both eye-popping returns and warnings of extreme volatility. Powered by Token Metrics’ AI insights, here’s a detailed look at where Launchcoin stands today.

🚀 AI Detected the Breakout Early

On April 20, 2025, Token Metrics’ proprietary AI model flipped bullish on Launchcoin. Since then, the token has rallied over 3x, proving the strength of the signal. Backed by machine learning models that track on-chain data, sentiment, and price action across multiple timeframes, the Trader Grade for Launchcoin is currently at a whopping 93.15%, designating it a Strong Buy in the short term.

However, after such an exponential surge, the platform’s analysts expect natural pullbacks as early buyers and whales begin to take profits. These corrections are healthy and expected in any meteoric price run—and should not be confused with a loss of fundamental strength.

🧠 Token Metrics Investor Grade: A Balanced Perspective

While short-term indicators are overwhelmingly bullish, the Investor Grade remains neutral, pointing to a more measured view on Launchcoin’s long-term potential. This signals that while there’s momentum, there are still structural risks—particularly due to its meme coin characteristics and reliance on hype cycles.

Still, a neutral long-term grade isn’t bearish. It suggests Launchcoin is currently stable at its elevated valuation, but investors should monitor developments carefully—especially as new features and ecosystem growth unfold.

📈 Launchcoin’s Wild Ride: From 54 SOL to $4 Million

The Launchcoin story has already minted millionaires. One trader reportedly turned an $8,191 investment (54 SOL) into $4 million after purchasing 14.62 million LAUNCHCOIN tokens when the market cap was below $500,000. This kind of exponential return is rare—even in crypto—and helped drive speculative interest across social media and trading forums.

Within just 22 days, Launchcoin’s market cap crossed $300 million, illustrating how quickly meme-based projects can capture market momentum, especially when they ride the wave of a compelling narrative.

🔄 Listings and Market Access

Launchcoin’s liquidity and accessibility have improved significantly. The token is now trading on major centralized exchanges:

  • Spot listings: Bitget, KuCoin, Gate.io, and MEXC
  • Futures: Recently launched on ByBit

These listings have broadened exposure, attracting a wider investor base and allowing leveraged traders to participate. Increased liquidity also reduces slippage, enabling larger capital inflows while minimizing execution risk.

🎭 From PASTERNAK to LAUNCHCOIN: The Rebranding

Initially launched as PASTERNAK, named after Believe’s founder Ben Pasternak, the project was rebranded to Launchcoin on May 2, 2025. The new name better reflects its core value proposition: empowering creators to launch tokens through a SocialFi model.

The model is simple but revolutionary—anyone can create a token by posting on social media with the “@launchcoin” tag. This lowers the barrier for entry into token creation and adds viral potential to every social interaction.

🧨 Risk and Volatility: A Speculative Bet

Despite its recent success, Launchcoin remains a highly speculative asset. Its meteoric rise is reminiscent of meme coin cycles seen with tokens like PEPE or DOGE. While Launchcoin offers a unique utility layer with its token-creation feature, its current valuation includes a significant hype premium.

Token Metrics encourages traders to stay nimble. With the AI trading signals, users can track grade changes in real-time, ensuring they’re not caught off guard by sharp reversals or cooldowns.

🧠 Final Thoughts

Launchcoin represents a blend of viral marketing, social token innovation, and AI-predicted trading opportunity. With strong short-term momentum, neutral long-term positioning, and significant ecosystem buzz, it’s a token to watch—but not without caution.

Whether you’re a trader riding the momentum or an investor assessing long-term viability, Token Metrics provides the data-driven edge to navigate Launchcoin’s volatility with confidence.

Research

Best Long-Term Crypto Picks for the 2025 Bull Market

Token Metrics Team
4 min
MIN

In a market full of noise, value investors are asking one critical question: what should I hold long-term?

Here are some of our top picks, based on fundamentals, traction, and longevity.

1. Grass – AI + Revenue

Grass stands out in the AI space. With over $15M in revenue from its browser extension and data resale model, it’s one of the few protocols generating real-world value. It’s a top AI blue chip we’re confident holding over multiple cycles.

2. Peaq – DePIN Infrastructure

Peaq positions itself as the Chainlink of decentralized physical infrastructure. While still under $1B FDV, it’s been consistent in development and narrative strength.

3. Sui – Consumer-Focused L1

Sui isn’t just another L1. Between Phantom wallet support, SuiPlay hardware, and growing dApp adoption, Sui has the elements to outpace older chains like Solana or Avalanche in user growth.

4. Parcl – Real Estate Derivatives

For exposure to real-world assets, Parcl offers a compelling play. Their UI is retail-friendly, listings are strong, and the market cap remains under $150M. This is one to watch as RWA adoption grows.

5. BitTensor – AI Infrastructure Layer

With a unique emission model and growing subnet usage, BitTensor remains the top AI infra token. Some even compare its long-term potential to early Bitcoin.

Bonus Mentions:

  • Uniswap / Aave / Compound – battle-tested DeFi with upcoming fee-sharing upgrades

  • Chainlink – oracle king still dominating infrastructure

  • Hyperliquid – sustainable revenue, EVM chain, and perps dominance

Final Words

The 2025 bull market will create noise—but also opportunity. These tokens aren’t just trendy—they’re infrastructure plays with real utility and upside. Allocate accordingly.

Research

SUI Price Analysis: Short-Term Momentum Builds Amid Long-Term Uncertainty

Token Metrics Team
4 min
MIN

SUI, a rising Layer 1 blockchain network, has been gaining traction recently—and Token Metrics' AI-powered tools were ahead of the curve in identifying its bullish momentum. On April 24th, the Token Metrics Trader Grade issued a bullish signal for SUI, and since then, the price has climbed nearly 22%, confirming the strength of the short-term trend.

But there’s more to this move than just price action. Token Metrics offers a unique perspective by analyzing both short-term and long-term signals through its proprietary Trader Grade and Investor Grade ratings. These grades offer a layered view of an asset's potential by using machine learning to evaluate over 80 on-chain, off-chain, and technical indicators.

Token Metrics AI: Bullish for Traders, Bearish for Investors

As of the latest data, SUI holds a “Strong Buy” rating on the Token Metrics Trader Grade, signaling powerful momentum for short-term traders. This suggests that swing traders and scalpers could benefit from the current trend, particularly if the price can decisively break through the immediate resistance at $4.25.

However, the Investor Grade tells a different story. While the short-term outlook is bullish, the long-term view remains cautious. The Investor Grade currently recommends a Sell, suggesting SUI may face challenges in sustaining gains over a multi-month time frame. This divergence highlights the importance of aligning your investment strategy with the appropriate time horizon.

TVL Growth Validates SUI’s Ecosystem Expansion

Beyond AI ratings, Token Metrics also factors in fundamental metrics—and one of the strongest tailwinds for SUI right now is its rapidly growing Total Value Locked (TVL). According to DeFi Llama, SUI’s TVL has surged to a new all-time high of $2.11 billion, cementing its position as the 8th largest blockchain by TVL.

This growth in TVL indicates that more capital is being deployed in the SUI ecosystem. It reflects increased user engagement with decentralized applications (dApps) on the network and signals rising confidence among DeFi participants. From a fundamental standpoint, this bodes well for SUI’s long-term utility—even if its price action hasn't yet caught up to the full extent of this growth.

Key Technical Levels: Breakout or Pullback?

From a technical analysis standpoint, SUI is now testing a major resistance at $4.25. A confirmed breakout above this level could send the asset surging toward new all-time highs, potentially igniting a new wave of momentum-driven buying.

However, if the price fails to breach this resistance zone, a pullback is likely. In that scenario, the $3.00 to $3.20 range should act as a solid support area. These levels will be critical for traders to monitor, and Token Metrics' real-time alerts can help users stay on top of such breakouts or reversals.

Trading Smarter with Token Metrics

Whether you're trading short-term breakouts or evaluating long-term positions, Token Metrics helps crypto investors make data-driven decisions. The platform’s dual-grade system—Trader Grade for momentum-based insights and Investor Grade for long-term trends—equips users with nuanced information to act with confidence.

Moreover, Token Metrics integrates this data directly into its AI Trading Agent and custom alerts system, ensuring you never miss an opportunity or warning signal. With instant access to heatmaps, technical breakdowns, and AI-based predictions, SUI traders can manage risk more efficiently and capitalize on emerging trends before the rest of the market catches on.

Final Thoughts

SUI is showing promising signs, especially with its network fundamentals improving rapidly and short-term momentum turning bullish. Still, the cautious long-term outlook suggests that traders should proceed with a balanced approach—watching both breakout levels and support zones, while leveraging tools like Token Metrics for real-time decision-making support.

As always, combining AI-driven insights with strong risk management is the key to navigating volatile markets like crypto. SUI is one to watch—and Token Metrics helps you stay one step ahead.

Announcements

AI Tokens and DeFi 2.0: Where Smart Capital is Flowing

Token Metrics Team
4 min
MIN

The crypto market is cyclical—not just in price, but in narrative. In recent months, attention has rotated from AI to DeFi, creating new opportunities for savvy investors. Let’s break down the trends.

AI Momentum Remains Strong

Projects like Vader AI, BitTensor, and Grass continue to dominate the conversation. Vader AI, part of the Virtua ecosystem, gained momentum from staking programs and Genesis Launchpad allocations. Grass, a data-layer AI protocol, claims $15M+ in revenue and recently flipped bullish on technical indicators.

BitTensor remains the leading infrastructure play in the AI space, drawing parallels to Bitcoin in its community enthusiasm and decentralization ethos. It has rebounded over 150% from its lows and is showing resilience in the current market cycle.

DeFi’s Comeback: Aerodrome and Beyond

Meanwhile, DeFi is showing signs of resurgence. Aerodrome, a DEX on the Base chain, is gaining traction through strong liquidity incentives and revenue-sharing mechanisms. Its user incentives echo the early days of Curve or Uniswap but on a chain optimized for scalability.

Virtua’s staking model is also driving a hybrid DeFi/AI strategy, blurring the lines between token utility, participation, and value capture.

Narrative Rotation: What It Means

Crypto narratives are rarely zero-sum. What we’re seeing now is a healthy diversification: AI remains dominant, but DeFi is catching a second wind. For investors, this means exploring tokens that sit at the intersection—offering strong tech, compelling incentives, and infrastructure integrations.

Closing Thoughts

Whether you’re riding the AI wave or positioning for the DeFi rebound, it’s clear that smart capital is flowing into ecosystems with tangible traction. Watch the flows, track the signals, and always be ready to pivot.

Track the Trends with Token Metrics

Token Metrics is your edge in navigating the ever-shifting landscape of crypto narratives. Our AI-powered research platform helps you spot bullish trends early, evaluate project fundamentals, and make data-driven investment decisions. Whether you're interested in AI tokens, DeFi protocols, or hybrid plays, Token Metrics provides real-time signals, technical grades, and curated indices to guide your next move.

Explore the platform at www.tokenmetrics.com and discover where smart capital is heading next.

Research

How Hyperliquid is Redefining Decentralized Perpetuals in 2025

Token Metrics Team
4 min
MIN

While most exchanges compete on liquidity or UI, Hyperliquid is rewriting the rules entirely.
This decentralized perps exchange has not only survived the bear market—it’s thriving. Backed by real revenue, a growing user base, and a unique listing model, Hyperliquid is emerging as the “Uniswap of Perps.”

The Reverse Auction Listing System

Hyperliquid introduces a novel reverse auction system for listing tokens. Bidders compete for tickers, with starting prices set at 2x the previous auction. Some tickers have fetched over $1 million, with the fees used for buybacks and burns—driving long-term value to the ecosystem.

This model isn’t just a gimmick. It introduces scarcity and gamification into token listings—something no other exchange is doing at this level.

Sustainable Revenue and Strong UX

Unlike many DEXs, Hyperliquid generates consistent trading fees, even in sideways markets. Its EVM-compatible L1 is coming soon, which could further cement it as the go-to perps exchange for serious traders.

Product-Market Fit in Action

In a space where hype often outpaces adoption, Hyperliquid offers both. It's not trying to be first—it's trying to be the best. The community listing process, upcoming L1, and high trading volumes all suggest it’s built for long-term relevance.

Smarter Trading with Token Metrics

To navigate emerging platforms like Hyperliquid, sophisticated analytics are key. Token Metrics provides a powerful suite of tools—AI-driven trading signals, token grades, on-chain data, and market indicators—to help traders make confident, data-backed decisions. Whether you're evaluating new token listings, monitoring market sentiment, or comparing DEX performance, Token Metrics equips you with everything you need to stay ahead of the curve.

Final Take

Hyperliquid is more than just another DEX—it’s a case study in how to build sustainable tokenomics and community alignment. If you’re looking for the next big infrastructure play in trading, don’t sleep on this one. And if you want to trade smarter, platforms like Token Metrics can be your secret weapon in decoding the market's next moves.

Announcements

Is Sui the Next Solana? A Deep Dive into L1 Competitors

Token Metrics Team
4 min
MIN

As the Layer 1 (L1) narrative continues to evolve, one blockchain has rapidly emerged as a serious contender to Solana’s throne: Sui. With growing infrastructure support and a strong focus on user experience, Sui is positioning itself as one of the most compelling L1 platforms in 2025.

Why the Sui Hype?

Sui has been gaining traction due to key integrations across the crypto ecosystem. Phantom wallet, known for its Solana roots, recently announced Sui support—putting Sui directly in the hands of thousands of users. Similarly, Axelar and LI.FI, major players in bridging and routing, have added Sui to their networks.

These integrations are not just symbolic; they’re strategic. By positioning itself as a supported chain across EVM-native infrastructure, Sui becomes more accessible and developer-friendly—critical factors for long-term adoption.

The SuiPlay Effect

Sui is also expanding beyond traditional DeFi and into consumer crypto. SuiPlay, a gaming-focused hardware device launched earlier this year, sold out in days. It marks a shift in L1 differentiation—no longer just about TPS (transactions per second), but about vertical-specific UX.

The gaming angle aligns with Sui’s broader push toward being the “consumer chain,” capturing not only dApp developers but also everyday users seeking smoother, gamified blockchain experiences.

Performance and Market Sentiment

Price action also favors Sui. While Solana bounced impressively from its post-FTX lows, Sui is now showing similar potential—with infrastructure support, developer traction, and consumer-facing products driving upward momentum.

The market seems to agree. Multiple indicators suggest Sui could outperform both Solana and Ethereum in the upcoming cycle. Its lower starting valuation also offers more upside, especially for value investors looking for the “next Solana.”

Final Thoughts

While it’s too early to crown Sui the definitive winner, all signs point to a strong L1 contender. Between integrations, product expansion, and market sentiment, Sui is carving a path worth watching—and potentially investing in.

Track Sui’s Momentum with Token Metrics

At Token Metrics, our AI-powered analytics tools help you track emerging L1 narratives like Sui in real time. From grade-based investment ratings and on-chain indicators to AI-generated bullish/bearish signals and technical scorecards, Token Metrics gives you the data you need to make smarter decisions. Explore Sui’s performance, compare it to other L1s, and stay ahead of the next market rotation—all in one dashboard.

Announcements

Launch Coin and the Rise of Internet Capital Markets

Token Metrics Team
3 min
MIN

In crypto, narratives evolve quickly—and in May 2025, a new one has captured the spotlight: Internet Capital Markets (ICM). At the center of this trend is a project called Launchcoin, which has surged over 20x in just days. But what is Launchcoin, and is this a sustainable movement or just another speculative wave?

What is Launchcoin?

Launchcoin is a protocol that lets users tokenize ideas directly from social platforms like X (formerly Twitter). Simply replying to a post with “@launchcoin + [your coin name]” can trigger the launch of a new token. The concept taps into the virality of meme coins but attempts to systematize it—making anyone with an idea a potential coin founder.

The recent buzz around Launchcoin follows a model that resembles earlier social-token projects like Clankerbot, but this one adds frictionless UX and a mobile-first approach. Some are already calling it “the TikTok of token launches.”

Is This Sustainable?

The token’s valuation surged from $0.01 to $0.24, with an FDV nearing $240M. Despite the meteoric rise, it’s worth noting that most of the current activity is speculative. At this stage, we view Launchcoin more as a trade than a long-term investment.

There are warning signs too: limited website traffic, sparse social engagement beyond one viral post, and no clear roadmap. While it’s grabbing headlines, it’s unclear how sticky this platform will be without deeper utility.

The Bigger Picture: Internet Capital Markets

Launchcoin is just the first ripple in a broader trend. ICM refers to the blending of social influence, capital formation, and blockchain—making it possible for ideas to become tradable assets in minutes. It reflects a growing appetite for spontaneous, viral, and community-led funding mechanisms.

While this space is still in its infancy, it hints at a future where capital formation isn't reserved for VCs and big-name founders but is democratized across the internet.

Final Thoughts

Launchcoin is exciting—but also risky. As with many meme-era projects, early gains may be followed by sharp corrections. Still, the rise of ICM is a signal worth watching. If future protocols can combine virality with compliance and utility, we could be witnessing the next evolution in how projects are launched—and who gets to launch them.

How Token Metrics Help You Track Emerging Narratives Like ICM

As crypto narratives evolve rapidly, tools like Token Metrics help investors stay ahead of the curve. Our platform uses AI-driven data, technical signals, and project ratings to detect early momentum in tokens like Launchcoin. With features like Bullish/Bearish Signals, Trader and Investor Grades, and curated narrative-based indices, Token Metrics enable users to evaluate trends like Internet Capital Markets with speed and precision. Whether you’re trading the hype or tracking long-term shifts, Token Metrics give you the insights needed to navigate the noise.

Crypto Basics

Ripple XRP Price Prediction: What’s Next for XRP After Its Bullish Breakout?

Token Metrics Team
3 min
MIN

Ripple (XRP) has been back in the spotlight after recent market moves—and investors are wondering: Will XRP keep going up? With a 15% surge since April 24 and growing optimism around XRP Futures ETFs, the sentiment is clearly shifting. Here's a breakdown of the latest XRP price prediction using data-driven insights from Token Metrics’ AI indicators and technical charts.

🚀 XRP Turned Bullish Before the ETF News

On April 24, Token Metrics’ proprietary AI trading indicator flashed a bullish signal on XRP—just before the approval of the ProShares XRP Futures ETF. This early signal positioned traders ahead of the 15% rally that followed.

Such predictive accuracy boosts trader confidence, especially during key market events. It reinforces the value of AI-driven trading signals in volatile crypto environments.

📊 TM Trader Grade: 88.84% – Bulls Are in Control

As of now, Token Metrics’ Trader Grade for XRP stands at a high 88.84%, signaling a strong buy. This grade reflects short-term momentum and trader sentiment, confirming that bulls currently dominate XRP’s price action.

Meanwhile, the Investor Grade—which tracks long-term fundamentals and trends—remains neutral. This suggests that while XRP is hot in the short term, long-term investors should remain cautiously optimistic.

📉 XRP Technical Analysis: Range-Bound but Primed for Breakout?

From a technical standpoint, XRP has traded sideways since December, forming a wide consolidation pattern. Key levels to watch:

  • Support: ~$2
  • Resistance: ~$2.86

This range has held for months, but with renewed interest and bullish sentiment, a breakout above $2.86 could trigger a much larger move. Traders should watch volume and ETF-related news for confirmation.

🧠 What’s Driving XRP’s Momentum?

  • XRP Futures ETF Approval: A major catalyst that validates institutional interest in Ripple.
  • AI-Powered Bullish Signal: Token Metrics’ indicators detected momentum before the market reacted.
  • Strong Buy Rating: A near-89% trader score indicates high conviction.

🔮 Ripple XRP Price Prediction – 2025 Outlook

With institutional products like ETFs emerging and short-term momentum picking up, XRP may soon test and potentially break above its current resistance. If bullish momentum continues:

  • Short-term price prediction: Retest of $2.86 and potential breakout toward $3+
  • Long-term outlook: Sideways consolidation remains until fundamentals or macro trends shift

✅ Conclusion: XRP Is Heating Up—But Caution Is Warranted

While XRP is showing bullish short-term potential, the long-term picture is still neutral. Traders should watch for confirmation above resistance and keep an eye on volume and ETF developments.

For more AI-powered crypto price predictions, trading signals, and investment insights, explore Token Metrics.

Announcements

Best Crypto Wallet: A Comprehensive Guide for 2025

Token Metrics Team
3 min
MIN

In the fast-paced world of cryptocurrency, choosing the best crypto wallet is critical for safeguarding your digital assets. Whether you're a beginner or a seasoned investor, the right wallet balances security, usability, and compatibility with your investment goals.

At Token Metrics, we help investors make smarter decisions using AI-powered insights—and that starts with understanding the foundation of crypto storage.

What Is a Crypto Wallet?

A crypto wallet is a digital tool that allows you to store, send, and receive cryptocurrencies like Bitcoin, Ethereum, and thousands of altcoins. These wallets don’t store your coins directly, but rather your private keys, which give you access to your funds on the blockchain.

There are two primary categories:

  • Hot Wallets: Connected to the internet (e.g., mobile apps, browser extensions)
  • Cold Wallets: Offline and more secure (e.g., hardware wallets)

Top Features to Look for in the Best Crypto Wallet

Choosing the best crypto wallet depends on your needs, but here are key features every good wallet should have:

  • Security: Look for multi-signature support, biometric authentication, and backup recovery phrases.
  • Compatibility: It should support your preferred cryptocurrencies and DeFi apps.
  • User Interface: A clean, intuitive interface makes navigation easy, especially for beginners.
  • Control: Non-custodial wallets give you full control of your keys and assets.
  • Support for NFTs and dApps: As Web3 expands, these are essential for power users.

Top 3 Crypto Wallets in 2025

1. MetaMask

A widely used browser extension and mobile wallet ideal for Ethereum and EVM-compatible chains. MetaMask is beginner-friendly and integrates seamlessly with dApps.

2. Ledger Nano X

A top-rated cold wallet offering unmatched security. It supports over 5,000 coins and connects via Bluetooth to mobile apps, balancing convenience with protection.

3. Trust Wallet

A mobile-first hot wallet with support for multiple blockchains, NFTs, and staking. It’s open-source and backed by Binance, making it a reliable choice for everyday use.

How to Use Token Metrics with Your Crypto Wallet

Once you’ve selected the best crypto wallet, connect it to Token Metrics to unlock deeper insights:

  • Track portfolio performance in real time
  • Receive AI-powered buy/sell signals
  • View historical ROI and risk metrics
  • Access research reports on wallet-compatible tokens

Whether you're exploring DeFi, trading altcoins, or holding long term, integrating Token Metrics with your wallet takes your crypto strategy to the next level.

Final Thoughts

The best crypto wallet is the one that aligns with your investment strategy, risk tolerance, and technical comfort level. As the crypto ecosystem grows, having a reliable wallet is no longer optional—it’s essential.

Make the right choice, protect your assets, and invest with confidence using AI-driven insights from Token Metrics.

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