Token Metrics MCP Server
Token Metrics MCP Server
README
Token Metrics MCP Server
The Token Metrics Model Context Protocol (MCP) server provides comprehensive cryptocurrency data, analytics, and insights through function calling. This server enables AI assistants and agents to access Token Metrics' powerful API for real-time crypto market data, trading signals, price predictions, and advanced analytics.
Features
- Real-time Crypto Data: Access current prices, market cap, volume, and other key metrics
- Trading Signals: AI-generated trading signals for long and short positions
- Price Predictions: Advanced price forecasting and scenario analysis
- Technical Analysis: Support and resistance levels, correlation analysis
- Market Analytics: Comprehensive market insights and sentiment analysis
- Quantitative Metrics: Advanced quantitative analysis and grading systems
Quick Start
Using npx (Recommended)
The easiest way to get started is using npx:
# Set environment variable and run
export TOKEN_METRICS_API_KEY=your_api_key_here
npx -y @token-metrics-ai/mcp@latest
Setup with AI Clients
Claude Desktop or VS Code/Cursor
Add the following to your claude_desktop_config.json or mcp.json:
{
"mcpServers": {
"token-metrics": {
"command": "npx",
"args": ["-y", "@token-metrics-ai/mcp@latest"],
"env": {
"TOKEN_METRICS_API_KEY": "YOUR_API_KEY"
}
}
}
}
Available Tools
The Token Metrics MCP server provides the following tools:
Token Data & Prices
get_tokens_data- Fetch comprehensive token informationget_tokens_price- Get current token pricesget_tokens_hourly_ohlcv- Hourly OHLCV dataget_tokens_daily_ohlcv- Daily OHLCV data
Trading & Analysis
get_tokens_trading_signal- AI-generated trading signalsget_tokens_trader_grade- Short-term trader gradesget_tokens_investor_grade- Long-term investor gradesget_tokens_resistance_and_support- Technical support/resistance levelsget_tokens_correlation- Token correlation analysis
Market Intelligence
get_market_metrics- Overall market analyticsget_sentiment- Market sentiment analysisget_tokens_quant_metrics- Quantitative metricsget_tokens_scenario_analysis- Price prediction scenarios
Research & Reports
get_tokens_ai_report- AI-generated token reportsget_crypto_investors- Crypto investor informationget_top_tokens_by_market_cap- Top tokens by market cap
Indices & Portfolio
get_indices- Fetch active and passive crypto indicesget_indices_performance- Historical performance data for indicesget_indices_holdings- Current holdings and weights for indices
Getting Your API Key
- Visit Token Metrics
- Sign up for an account
- Navigate to your API Dashboard
- Generate a new API key
- Use the API key with this MCP server
Development
Prerequisites
- Node.js 18 or higher
- npm or yarn
- TypeScript
Local Development
- Clone the repository:
git clone https://github.com/token-metrics/mcp.git
cd mcp
- Install dependencies:
npm install
- Set your API key:
export TOKEN_METRICS_API_KEY=your_api_key_here
- Run in development mode:
npm run start:dev
Building
npm run build
Testing with MCP Inspector
You can test the server using the MCP Inspector:
# Build the server first
npm run build
# Run with MCP Inspector
npx @modelcontextprotocol/inspector node build/src/cli.js
Configuration
The server accepts the following configuration options:
--help- Show help information
Environment variables:
TOKEN_METRICS_API_KEY- Your Token Metrics API key
Error Handling
The server includes comprehensive error handling:
- Invalid API Key: Returns authentication error
- Rate Limiting: Handles API rate limits gracefully
- Network Issues: Retries failed requests
- Invalid Parameters: Validates input parameters
Security
- API keys are handled securely
- No sensitive data is logged
- Docker container runs as non-root user
- Input validation on all parameters
Support
- Documentation: Token Metrics API Docs
- Issues: GitHub Issues
- Support: Token Metrics Support
License
MIT License - see LICENSE file for details.
<a href="https://glama.ai/mcp/servers/@token-metrics/mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@token-metrics/mcp/badge" /> </a>
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。