{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-token-metrics","slug":"token-metrics","name":"Token Metrics","type":"mcp","url":"https://github.com/token-metrics/mcp","page_url":"https://unfragile.ai/token-metrics","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-token-metrics__cap_0","uri":"capability://data.processing.analysis.real.time.cryptocurrency.price.and.market.data.retrieval","name":"real-time cryptocurrency price and market data retrieval","description":"Fetches current and historical cryptocurrency price data, market capitalization, trading volumes, and market metrics through standardized MCP tool interface (get_tokens_price, get_tokens_data, get_market_metrics). The system acts as a middleware layer translating MCP tool calls into authenticated HTTP requests to the Token Metrics API, caching responses to reduce latency and API quota consumption. Supports batch queries for multiple tokens and configurable time windows.","intents":["I need to get the current price of Bitcoin and Ethereum for my trading bot","I want to fetch historical price data for the last 30 days for multiple cryptocurrencies","I need market cap and trading volume metrics to analyze market trends","I want to integrate live crypto prices into my AI assistant's decision-making"],"best_for":["AI agents building crypto trading systems","Developers creating cryptocurrency dashboards","Teams building LLM-powered market analysis tools","Crypto portfolio management applications"],"limitations":["API rate limits apply based on Token Metrics subscription tier — may throttle high-frequency queries","Historical data depth depends on Token Metrics API plan — free tier may have limited lookback windows","Real-time data has inherent latency from Token Metrics data sources (typically 1-5 minute delay)","No local caching persistence — requires external state store for multi-session data retention"],"requires":["Node.js 18.0.0+","Active Token Metrics API key","Network connectivity to Token Metrics API endpoints","MCP client compatible with stdio, HTTP/SSE, or OpenAI transports"],"input_types":["token symbol (string, e.g., 'BTC', 'ETH')","time window parameters (ISO 8601 dates or relative periods)","batch token arrays"],"output_types":["JSON structured market data (price, volume, market cap, change percentages)","time-series price arrays","aggregated market metrics"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_1","uri":"capability://data.processing.analysis.trading.signal.generation.and.trader.performance.grading","name":"trading signal generation and trader performance grading","description":"Generates actionable trading signals (buy/sell/hold recommendations) and grades trader performance using Token Metrics' proprietary algorithms through get_tokens_trading_signal and get_trader_grade tools. The system wraps Token Metrics' signal generation engine, returning structured recommendations with confidence scores and historical accuracy metrics. Signals are computed server-side and delivered as JSON payloads containing signal type, strength, and supporting rationale.","intents":["I want to get buy/sell signals for a specific cryptocurrency to inform my trading decisions","I need to evaluate the historical accuracy of a trader's recommendations","I want to integrate automated trading signals into my AI agent's decision pipeline","I need to compare signal quality across multiple tokens to identify opportunities"],"best_for":["Algorithmic traders building signal-driven bots","AI agents making autonomous trading decisions","Crypto portfolio managers evaluating trader performance","Risk assessment systems requiring signal confidence metrics"],"limitations":["Signal accuracy depends on Token Metrics' underlying model quality — no guarantee of profitability","Signals are point-in-time snapshots; market conditions can invalidate recommendations within minutes","Trader grading requires historical data that may not be available for newly-tracked traders","No custom signal weighting or ensemble methods — uses Token Metrics' fixed algorithm"],"requires":["Node.js 18.0.0+","Token Metrics API key with trading signal access tier","Network connectivity to Token Metrics API","MCP client implementation"],"input_types":["token symbol (string)","trader identifier (string or numeric ID)","optional time window for historical grading"],"output_types":["JSON signal object (signal_type: 'BUY'|'SELL'|'HOLD', confidence: 0-100, rationale: string)","trader grade object (overall_score, accuracy_rate, win_rate, historical_performance)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_10","uri":"capability://safety.moderation.api.key.authentication.with.environment.variable.and.http.header.support","name":"api key authentication with environment variable and http header support","description":"Implements flexible API key authentication supporting both environment variables (for CLI/local deployment) and HTTP headers (for HTTP/OpenAI transports). The system validates API keys at server startup for CLI mode and on each request for HTTP modes, returning 401 Unauthorized if key is missing or invalid. Authentication is decoupled from tool implementations, allowing tools to assume authenticated context.","intents":["I want to authenticate my local CLI server using an environment variable","I need to pass API keys securely via HTTP headers to the hosted server","I want to validate API keys before executing expensive tool calls","I need to support multiple authentication methods for different deployment scenarios"],"best_for":["Developers deploying Token Metrics MCP locally","Teams hosting HTTP/OpenAI transports in production","Security-conscious organizations requiring key rotation","Multi-tenant deployments requiring per-client authentication"],"limitations":["Environment variables are visible in process listings — not suitable for shared systems","HTTP headers are transmitted in plaintext unless HTTPS is used — requires external reverse proxy for TLS","No key rotation mechanism — requires server restart to update keys","No per-tool authentication — all tools share same API key"],"requires":["Token Metrics API key (from Token Metrics dashboard)","For CLI: TOKEN_METRICS_API_KEY environment variable set","For HTTP: x-api-key HTTP header on all requests","For OpenAI: Token Metrics API key configured in OpenAI integration"],"input_types":["API key string (from Token Metrics dashboard)"],"output_types":["Authentication success/failure status","401 Unauthorized error if key is invalid"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_11","uri":"capability://automation.workflow.docker.and.kubernetes.deployment.with.ci.cd.pipeline","name":"docker and kubernetes deployment with ci/cd pipeline","description":"Provides production-ready Docker images and Kubernetes manifests for deploying Token Metrics MCP server at scale. The system includes multi-stage Dockerfile for optimized image size, Kubernetes deployment/service/ingress manifests for orchestration, and CI/CD pipeline (GitHub Actions) for automated testing and image publishing. Deployment supports environment variable configuration, health checks, and resource limits.","intents":["I want to deploy Token Metrics MCP server as a Docker container","I need to run Token Metrics MCP on Kubernetes for high availability","I want to automate testing and image publishing via CI/CD","I need to configure resource limits and health checks for production"],"best_for":["DevOps teams deploying Token Metrics MCP in production","Organizations running Kubernetes clusters","Teams requiring automated CI/CD pipelines","Multi-tenant deployments requiring horizontal scaling"],"limitations":["Docker image size may be large if not optimized — requires multi-stage build","Kubernetes manifests are templates — require customization for specific environments","CI/CD pipeline is GitHub Actions-specific — requires migration for other CI systems","No built-in service mesh integration — requires external tools for advanced networking"],"requires":["Docker 20.10+ for building/running containers","Kubernetes 1.20+ for orchestration (optional)","GitHub repository for CI/CD pipeline (optional)","Container registry (Docker Hub, ECR, GCR, etc.) for image storage"],"input_types":["Dockerfile (for building images)","Kubernetes manifests (YAML)","GitHub Actions workflow (YAML)"],"output_types":["Docker image (OCI format)","Kubernetes pods/services/ingress","CI/CD pipeline execution logs"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_12","uri":"capability://automation.workflow.http.sse.streaming.responses.for.long.running.operations","name":"http/sse streaming responses for long-running operations","description":"Implements HTTP Server-Sent Events (SSE) transport for streaming responses from long-running tool operations (scenario analysis, report generation). The system uses HTTP/SSE protocol to send partial results and progress updates to clients in real-time, avoiding request timeouts for expensive computations. Clients receive streaming JSON objects that can be processed incrementally as they arrive.","intents":["I want to stream results from long-running scenario analysis without timing out","I need to receive progress updates while Token Metrics generates AI reports","I want to process partial results incrementally as they arrive","I need to handle large result sets without loading everything into memory"],"best_for":["Web applications requiring real-time progress feedback","Clients with strict request timeout limits","Systems processing large result sets incrementally","AI agents needing streaming responses for long operations"],"limitations":["SSE is HTTP-only — not compatible with WebSocket or gRPC transports","Streaming adds complexity to client code — requires event listener implementation","No built-in error recovery — connection drops lose partial results","SSE has browser compatibility issues in older clients"],"requires":["HTTP client with SSE support (most modern browsers/libraries)","HTTP Server with SSE support (included in Node.js)","Network connectivity with no intermediate proxies blocking streaming"],"input_types":["HTTP POST request with tool call parameters"],"output_types":["Server-Sent Events stream (text/event-stream MIME type)","Streaming JSON objects (one per line)","Final result object with completion status"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_13","uri":"capability://tool.use.integration.openai.specific.function.calling.integration","name":"openai-specific function calling integration","description":"Implements OpenAI-compatible HTTP server that exposes Token Metrics tools as OpenAI function calling schemas. The system translates MCP tool definitions into OpenAI function calling format, handles OpenAI-specific request/response serialization, and manages function call execution within OpenAI's function calling workflow. Allows OpenAI API clients to call Token Metrics tools directly without MCP client implementation.","intents":["I want to use Token Metrics tools directly in OpenAI API function calling","I need to integrate Token Metrics data into my OpenAI-based AI agent","I want to avoid implementing MCP client code for OpenAI integrations","I need to expose Token Metrics tools to OpenAI's native function calling interface"],"best_for":["OpenAI API users wanting Token Metrics integration","Teams building OpenAI-based AI agents with crypto data","Developers avoiding MCP client implementation complexity","Organizations standardized on OpenAI API"],"limitations":["OpenAI-specific — not compatible with other LLM providers (Claude, Gemini, etc.)","Requires OpenAI API key in addition to Token Metrics API key","Function calling schema translation may lose some MCP tool metadata","OpenAI function calling has token limits — complex tools may exceed limits"],"requires":["Node.js 18.0.0+","Token Metrics API key","OpenAI API key","OpenAI Python/Node.js client library"],"input_types":["OpenAI function calling request (JSON)","Tool call parameters matching OpenAI schema"],"output_types":["OpenAI function calling response (JSON)","Tool execution result in OpenAI format"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_2","uri":"capability://data.processing.analysis.technical.analysis.with.resistance.support.and.correlation.metrics","name":"technical analysis with resistance, support, and correlation metrics","description":"Computes technical analysis indicators including resistance/support levels, price correlation between tokens, and momentum metrics through get_tokens_resistance_and_support and get_tokens_correlation tools. The system queries Token Metrics' technical analysis engine which performs statistical analysis on historical price data to identify key price levels and cross-token relationships. Results are returned as structured JSON containing price levels, confidence intervals, and correlation coefficients.","intents":["I need to identify resistance and support levels for a token to set stop-loss and take-profit orders","I want to find correlated tokens to understand portfolio risk and diversification opportunities","I need to analyze momentum indicators to time entry and exit points","I want to understand which tokens move together for pair trading strategies"],"best_for":["Technical traders building chart analysis tools","Portfolio managers analyzing correlation matrices","Risk management systems calculating portfolio beta","AI agents making timing-based trading decisions"],"limitations":["Technical analysis indicators are lagging — based on historical data, not predictive of future price action","Resistance/support levels are probabilistic estimates; price can break through with no warning","Correlation metrics are computed over fixed historical windows — correlations break down during market stress","No customizable lookback periods or indicator parameters — uses Token Metrics' fixed configurations"],"requires":["Node.js 18.0.0+","Token Metrics API key with technical analysis access","Network connectivity to Token Metrics API","MCP client"],"input_types":["token symbol (string)","optional time period for analysis window","token pair array for correlation analysis"],"output_types":["JSON resistance/support object (resistance_level: number, support_level: number, confidence: 0-100)","correlation matrix (token_pair: string, correlation_coefficient: -1 to 1, statistical_significance: boolean)"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_3","uri":"capability://data.processing.analysis.advanced.scenario.analysis.and.quantitative.metrics.computation","name":"advanced scenario analysis and quantitative metrics computation","description":"Performs scenario-based analysis and computes advanced quantitative metrics (Sharpe ratio, volatility, Value-at-Risk) through get_tokens_scenario_analysis and get_tokens_quant_metrics tools. The system executes server-side Monte Carlo simulations and statistical calculations on historical token data to project potential outcomes under different market conditions. Results include probability distributions, risk metrics, and performance projections returned as structured JSON.","intents":["I want to model how a token would perform under different market scenarios (bull/bear/sideways)","I need to calculate risk metrics like Sharpe ratio and volatility for portfolio optimization","I want to estimate Value-at-Risk (VaR) for a position to set risk limits","I need to run stress tests on my portfolio under extreme market conditions"],"best_for":["Quantitative traders building risk models","Portfolio managers performing scenario planning","Risk officers calculating regulatory capital requirements","AI agents making risk-adjusted investment decisions"],"limitations":["Scenario analysis assumes historical patterns repeat — tail risks and black swan events may not be captured","Monte Carlo simulations are computationally expensive — may have latency for complex scenarios","Quantitative metrics depend on historical data quality — garbage in, garbage out","No custom scenario definition — uses Token Metrics' predefined scenarios (bull/bear/sideways)"],"requires":["Node.js 18.0.0+","Token Metrics API key with advanced analytics tier","Network connectivity to Token Metrics API","MCP client"],"input_types":["token symbol (string)","scenario type (enum: 'BULL', 'BEAR', 'SIDEWAYS')","optional time horizon for projections","position size for VaR calculations"],"output_types":["JSON scenario analysis object (scenario_type: string, probability_distribution: array, expected_return: number, worst_case: number, best_case: number)","JSON quant metrics object (sharpe_ratio: number, volatility: number, var_95: number, max_drawdown: number)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_4","uri":"capability://data.processing.analysis.market.sentiment.and.social.signal.analysis","name":"market sentiment and social signal analysis","description":"Aggregates and analyzes market sentiment from social media, news, and on-chain data through get_sentiment and related tools. The system collects sentiment signals from multiple sources (Twitter/X, Reddit, news feeds, blockchain metrics) and computes aggregate sentiment scores using natural language processing and statistical aggregation. Results include sentiment polarity scores, trend direction, and source-specific breakdowns returned as JSON.","intents":["I want to gauge overall market sentiment for a token to validate my trading thesis","I need to detect sentiment shifts that might precede price movements","I want to identify which social platforms are most predictive of price action","I need to monitor sentiment trends over time to track community health"],"best_for":["Sentiment-driven traders building contrarian strategies","Community managers monitoring token reputation","AI agents incorporating social signals into decision-making","Market researchers analyzing community engagement"],"limitations":["Sentiment analysis is subjective and prone to manipulation (coordinated FUD/FOMO campaigns)","Social signals are lagging indicators — sentiment often follows price action, not precedes it","Sentiment data is noisy and requires filtering to remove bot activity and spam","No custom sentiment model — uses Token Metrics' fixed NLP pipeline"],"requires":["Node.js 18.0.0+","Token Metrics API key with sentiment analysis access","Network connectivity to Token Metrics API","MCP client"],"input_types":["token symbol (string)","optional time window for sentiment aggregation","optional source filter (social, news, on-chain)"],"output_types":["JSON sentiment object (overall_sentiment: -1 to 1, trend: 'BULLISH'|'BEARISH'|'NEUTRAL', confidence: 0-100, source_breakdown: {twitter: number, reddit: number, news: number, on_chain: number})"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_5","uri":"capability://text.generation.language.ai.generated.crypto.research.reports.and.analysis","name":"ai-generated crypto research reports and analysis","description":"Generates comprehensive AI-powered research reports on cryptocurrencies and market trends through get_tokens_ai_report tool. The system uses Token Metrics' LLM-based analysis engine to synthesize market data, technical analysis, sentiment, and fundamental metrics into narrative research reports. Reports include executive summaries, risk assessments, and investment theses returned as structured text with embedded data references.","intents":["I want a comprehensive research report on a token to understand its investment case","I need an AI-generated analysis of market trends to inform my strategy","I want to generate research reports for my clients without manual analysis","I need to validate my investment thesis against AI-generated analysis"],"best_for":["Investment advisors generating client reports","Crypto funds automating research workflows","AI agents synthesizing market intelligence into narratives","Retail investors seeking comprehensive token analysis"],"limitations":["AI-generated reports may contain hallucinations or unsupported claims — require human review before use","Reports are generated from Token Metrics' data sources only — may miss important external information","Report quality depends on underlying data quality — garbage in, garbage out","No customizable report templates or sections — uses Token Metrics' fixed report structure"],"requires":["Node.js 18.0.0+","Token Metrics API key with AI report access","Network connectivity to Token Metrics API","MCP client"],"input_types":["token symbol (string)","optional report type (enum: 'FUNDAMENTAL', 'TECHNICAL', 'SENTIMENT', 'COMPREHENSIVE')","optional focus areas (array of strings)"],"output_types":["JSON report object (title: string, executive_summary: string, sections: [{title: string, content: string, data_references: array}], risk_assessment: string, investment_thesis: string)"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_6","uri":"capability://data.processing.analysis.crypto.investor.and.fund.tracking","name":"crypto investor and fund tracking","description":"Tracks cryptocurrency investors, funds, and their portfolio holdings through get_crypto_investors tool. The system maintains a database of known crypto investors and funds, exposing their portfolio compositions, historical performance, and investment patterns. Results include investor profiles, holdings lists, and performance metrics returned as structured JSON.","intents":["I want to see what tokens a specific crypto fund is holding","I need to track the portfolio performance of top crypto investors","I want to identify which investors are accumulating a specific token","I need to analyze investor concentration risk for a token"],"best_for":["Investors tracking whale activity and fund positions","Portfolio managers benchmarking against peer funds","AI agents identifying smart money signals","Researchers analyzing investor behavior patterns"],"limitations":["Investor data is only as current as Token Metrics' last update — may lag actual portfolio changes by days","Not all investors are tracked — coverage depends on Token Metrics' data sources","Holdings data may be incomplete or estimated from on-chain activity","No real-time position updates — requires polling for latest data"],"requires":["Node.js 18.0.0+","Token Metrics API key with investor tracking access","Network connectivity to Token Metrics API","MCP client"],"input_types":["investor/fund identifier (string or numeric ID)","optional token symbol to filter holdings","optional time window for performance analysis"],"output_types":["JSON investor object (name: string, type: 'FUND'|'WHALE'|'INSTITUTION', holdings: [{token: string, amount: number, percentage: number}], performance: {ytd_return: number, aum: number})"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_7","uri":"capability://data.processing.analysis.cryptocurrency.indices.and.portfolio.performance.tracking","name":"cryptocurrency indices and portfolio performance tracking","description":"Provides access to cryptocurrency indices and portfolio performance metrics through get_indices and get_indices_performance tools. The system computes weighted indices across token baskets (market cap weighted, equal weighted, custom) and tracks portfolio performance against benchmarks. Results include index values, constituent weights, and performance attribution returned as JSON.","intents":["I want to track my portfolio performance against the crypto market index","I need to create a custom index of tokens for my investment strategy","I want to analyze which tokens are driving my portfolio's performance","I need to benchmark my returns against standard crypto indices (BTC dominance, etc.)"],"best_for":["Portfolio managers tracking benchmark performance","Index fund managers replicating crypto indices","AI agents making index-relative investment decisions","Researchers analyzing portfolio attribution"],"limitations":["Index performance is historical — past performance does not guarantee future results","Custom indices require manual definition — no automatic rebalancing","Index constituents may change over time — historical comparisons may not be apples-to-apples","No real-time index updates — indices are computed on fixed schedules"],"requires":["Node.js 18.0.0+","Token Metrics API key with indices access","Network connectivity to Token Metrics API","MCP client"],"input_types":["index identifier (string, e.g., 'BTC_DOMINANCE', 'MARKET_CAP_WEIGHTED')","optional custom index definition (token array with weights)","optional time window for performance calculation"],"output_types":["JSON index object (name: string, value: number, constituents: [{token: string, weight: number, contribution: number}], performance: {1d: number, 7d: number, 30d: number, ytd: number})"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_8","uri":"capability://tool.use.integration.multi.transport.mcp.server.with.cli.http.and.openai.integration","name":"multi-transport mcp server with cli, http, and openai integration","description":"Implements three distinct server transport modes (stdio CLI, HTTP/SSE, OpenAI-specific HTTP) from single codebase, allowing the same tool ecosystem to serve local development, web applications, and OpenAI integrations. The system uses MCP protocol's standardized tool schema to define tools once and expose them across all transports without code duplication. Each transport mode handles authentication, request routing, and response serialization independently while sharing core tool implementations.","intents":["I want to test Token Metrics tools locally using MCP Inspector before deploying","I need to expose Token Metrics tools to web applications via HTTP/SSE transport","I want to integrate Token Metrics tools directly into OpenAI's function calling API","I need to deploy the same tool ecosystem across multiple client types without code changes"],"best_for":["Developers building MCP-compatible AI applications","Teams deploying Token Metrics integration across multiple platforms","OpenAI API users wanting native Token Metrics integration","Organizations requiring both local development and cloud deployment"],"limitations":["CLI transport uses stdio — limited to local development and MCP Inspector, not suitable for production","HTTP transport requires external reverse proxy for HTTPS in production — no built-in TLS","OpenAI transport is OpenAI-specific — not compatible with other LLM providers","All transports share same rate limiting — high load on one transport affects others"],"requires":["Node.js 18.0.0+","Token Metrics API key","For HTTP transport: HTTP client compatible with SSE (Server-Sent Events)","For OpenAI transport: OpenAI API key and compatible client library"],"input_types":["MCP tool calls with standardized schema","HTTP POST requests with JSON payloads","OpenAI function calling requests"],"output_types":["MCP tool results (JSON)","HTTP/SSE responses (JSON with streaming support)","OpenAI function calling responses (JSON)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-token-metrics__cap_9","uri":"capability://tool.use.integration.standardized.mcp.tool.schema.definition.and.validation","name":"standardized mcp tool schema definition and validation","description":"Defines 21+ cryptocurrency analysis tools using MCP's standardized tool schema, providing consistent parameter validation, error handling, and response formatting across all tools. The system uses JSON schema to define tool inputs (required/optional parameters, types, constraints) and outputs (response structure, data types). Tool definitions are validated at server startup and used to generate OpenAI function calling schemas, HTTP endpoint documentation, and CLI help text automatically.","intents":["I want to understand what parameters each Token Metrics tool accepts","I need to validate tool inputs before calling them to catch errors early","I want to generate OpenAI function calling schemas from tool definitions","I need to auto-generate API documentation from tool definitions"],"best_for":["MCP client developers integrating Token Metrics tools","API documentation generators","OpenAI function calling integrations","Tool validation and error handling systems"],"limitations":["Schema validation is static — cannot validate complex business logic constraints","Tool definitions are read-only at runtime — cannot dynamically add/remove tools","Schema generation for OpenAI may require manual adjustments for complex types","No schema versioning — breaking changes require client updates"],"requires":["Node.js 18.0.0+","MCP client library compatible with tool schema","JSON schema validation library (included in MCP)"],"input_types":["MCP tool call with parameters matching schema","JSON schema definition (for tool definition)"],"output_types":["Validated tool parameters (JSON)","Tool execution result (JSON matching output schema)","OpenAI function calling schema (JSON)","Error messages with schema violation details"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":35,"verified":false,"data_access_risk":"high","permissions":["Node.js 18.0.0+","Active Token Metrics API key","Network connectivity to Token Metrics API endpoints","MCP client compatible with stdio, HTTP/SSE, or OpenAI transports","Token Metrics API key with trading signal access tier","Network connectivity to Token Metrics API","MCP client implementation","Token Metrics API key (from Token Metrics dashboard)","For CLI: TOKEN_METRICS_API_KEY environment variable set","For HTTP: x-api-key HTTP header on all requests"],"failure_modes":["API rate limits apply based on Token Metrics subscription tier — may throttle high-frequency queries","Historical data depth depends on Token Metrics API plan — free tier may have limited lookback windows","Real-time data has inherent latency from Token Metrics data sources (typically 1-5 minute delay)","No local caching persistence — requires external state store for multi-session data retention","Signal accuracy depends on Token Metrics' underlying model quality — no guarantee of profitability","Signals are point-in-time snapshots; market conditions can invalidate recommendations within minutes","Trader grading requires historical data that may not be available for newly-tracked traders","No custom signal weighting or ensemble methods — uses Token Metrics' fixed algorithm","Environment variables are visible in process listings — not suitable for shared systems","HTTP headers are transmitted in plaintext unless HTTPS is used — requires external reverse proxy for TLS","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.5,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:04.050Z","last_scraped_at":"2026-05-03T14:00:15.503Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=token-metrics","compare_url":"https://unfragile.ai/compare?artifact=token-metrics"}},"signature":"F8O7kxNfO5GNgfzcodXE5qWBUHvsdcAMbt03w459qo4bS85yR0kPf7bNIo3RNUxV7p+VKg4miuYhIBC9lGQsBg==","signedAt":"2026-06-22T10:43:01.131Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/token-metrics","artifact":"https://unfragile.ai/token-metrics","verify":"https://unfragile.ai/api/v1/verify?slug=token-metrics","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}