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MCP-Analytics-Middleware
Un middleware tipográfico liviano para servidores MCP SDK que ofrece análisis. Captura métricas de solicitud, datos de rendimiento y patrones de uso con una sobrecarga mínima. Cuenta con monitoreo en tiempo real, recopilación de datos configurable e informes detallados, todos con seguridad de tipo completo.
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MCP Analytics Middleware
A simple way to track and visualize how your MCP server is being used. See which tools are most popular, catch errors early, and understand your server's performance.
Features
- 🔍 Track all tool calls and resource requests
- 📊 See performance metrics and error rates
- 🌐 Web dashboard for live analytics
- 💾 SQLite database for persistent storage
Quick Start
- Install the package:
yarn add mcp-analytics-middleware
- Add it to your MCP server:
import { McpAnalytics } from 'mcp-analytics-middleware';
let server = new McpServer({
name: 'Sample MCP Server with Analytics',
version: '1.0.0'
});
const analytics = new McpAnalytics('analytics.db');
server = analytics.enhance(server); // override tool and resource function implementation to record usage in sqlite
Live Analytics
Want to see a dashboard for a Tyescript SDK MCP Server making use of this middleware? You can directly provide a live dashboard using
npx -p mcp-analytics-middleware web-viewer --db-path analytics.db
The web dashboard will open at http://localhost:8080 and show you live analytics!
You'll see:
- Total tool calls and resource requests
- Error rates and performance metrics
- Most used tools and slowest operations
Example Implementations
Example implementatinos of the analytics middleware can be found.
- Dummy Caluclator Server Example src/server.ts
- Ethereum RPC MCP Server with Analytics server/index.ts_
- Forked Verision of the Google Maps MCP Server with additional Analytics Middleware src/google-maps/index.ts
Running with Inspector
If you're using the MCP Inspector, just add the analytics flag:
yarn inspector --analytics --db-path analytics.db
License
MIT
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Reviews

user_LkxlCcdJ
As a dedicated user of mcp-analytics-middleware, I highly recommend it for anyone looking to streamline their data analytics processes. Developed by the talented Phillip-Kemper, this middleware integrates seamlessly with various applications, enhancing your data management capabilities. The user-friendly interface and robust functionality have significantly improved my workflow. Check it out on GitHub: https://github.com/Phillip-Kemper/mcp-analytics-middleware.