MCP Analytics Middleware: Real-Time Telemetry & Performance Insights

MCP Analytics Middleware: Lightweight TypeScript middleware for MCP SDKs, capturing real-time metrics, performance insights, and usage patterns—all type-safe with minimal overhead.

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About MCP Analytics Middleware

What is MCP Analytics Middleware: Real-Time Telemetry & Performance Insights?

MCP Analytics Middleware is a purpose-built tool for developers managing MCP servers, offering real-time visibility into tool usage, error detection, and performance metrics. Unlike generic monitoring solutions, it’s deeply integrated with MCP’s architecture to provide actionable insights. For instance, the SQLite-backed database ensures persistent storage while the web dashboard allows instant analysis of live data—ideal for environments where rapid iteration is critical.

How to use MCP Analytics Middleware: Real-Time Telemetry & Performance Insights?

Integration is straightforward: first install via Yarn, then attach the middleware to your server instance. The lightweight setup emphasizes developer productivity—no complex configurations required. To visualize data, choose between a CLI-based console or the interactive web interface (running at localhost:5000). A best practice is to pair it with MCP Inspector using the --db-path flag for seamless debugging workflows.

// Example server setup
import { McpAnalytics } from 'mcp-analytics-middleware';
const analytics = new McpAnalytics('analytics.db');
server.use(analytics.middleware);

MCP Analytics Middleware Features

Key Features of MCP Analytics Middleware: Real-Time Telemetry & Performance Insights?

Granular Tracking: Every tool call and resource request is logged, letting you identify which features are most used (e.g., tracking API endpoint popularity).
Proactive Error Detection: Real-time error aggregation helps catch issues before they impact users—a notable advantage for CI/CD pipelines.
API-Driven Analysis: The Analytics class exposes methods to fetch top-performing tools or slowest operations, useful for A/B testing infrastructure changes.

Use Cases for MCP Analytics Middleware

Common scenarios include:

Optimizing server resource allocation by identifying underused tools
Validating feature adoption rates post-deployment
Automating error reports to Slack via the webhooks API

MCP Analytics Middleware FAQ

Frequently Asked Questions

Does the database support scaling?
SQLite handles small-to-medium workloads well, but for enterprise use, consider exporting data to PostgreSQL via the export() method.

Why 5-second update intervals?
Striking a balance between real-time responsiveness and server load—this cadence works for most development environments.

Can I customize dashboard metrics?
Yes, the web UI supports adding/removing widgets via configuration files, though advanced customization requires modifying the source.

Content

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
🌐 Beautiful web dashboard for live analytics
💾 SQLite database for persistent storage
⚡ Real-time updates every 5 seconds

Quick Start

Install the package:

yarn add mcp-analytics-middleware

Add it to your MCP server:

import { McpAnalytics } from 'mcp-analytics-middleware';

const analytics = new McpAnalytics('analytics.db');
server.use(analytics.middleware);

View your analytics:

# Console view
yarn mcp-analytics-view --db-path=analytics.db

# Or check out the fancy web dashboard
yarn web-viewer --db-path=analytics.db

The web dashboard will open at http://localhost:5000 and show you live analytics!

Live Analytics

Want to see what's happening on your server right now? Just start the web viewer with your database path:

yarn web-viewer --db-path=analytics.db

You'll see:

Total tool calls and resource requests
Error rates and performance metrics
Most used tools and slowest operations
Daily usage patterns
And it all updates automatically every 5 seconds!

Running with Inspector

If you're using the MCP Inspector, just add the analytics flag:

yarn inspector --db-path=analytics.db

API Reference

McpAnalytics

The main class that handles everything.

class McpAnalytics {
  constructor(dbPath: string);
  middleware: Middleware;
  db: AnalyticsDB;
  analytics: Analytics;
}

AnalyticsDB

Handles all the database stuff.

class AnalyticsDB {
  getToolCallStats(): ToolStats;
  getResourceRequestStats(): ResourceStats;
}

Analytics

Gives you all the cool analytics calculations.

class Analytics {
  getTopTools(limit: number): ToolStats[];
  getSlowestTools(limit: number): ToolStats[];
  getErrorProneTool(limit: number): ToolStats[];
}

Development

# Install everything
yarn install

# Build the project
yarn build

# Start the development server
yarn dev

License

MIT

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