MCPcat
MCPcat is an analytics platform for MCP server owners π±.
What is MCPcat?
MCPcat is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to mcpcat is an analytics platform for mcp server owners π±.
MCPcat is an analytics platform for MCP server owners π±.
This server falls under the Analytics category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- MCPcat is an analytics platform for MCP server owners π±.
Use Cases
Maintainer
Works with
Installation
NPM
npx -y mcpcatManual Installation
npx -y mcpcatConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use MCPcat
MCPcat is an analytics SDK for MCP server developers that wraps any existing MCP server to capture tool call telemetry, user behavior patterns, session replays, and trace-level debugging data. Rather than being a standalone MCP server itself, it is a TypeScript library you integrate into your own server with a single function call β mcpcat.track(server, projectId) β giving you immediate visibility into how agents and users are interacting with your tools. It supports exporting telemetry to Datadog, Sentry, PostHog, and OTLP-compatible backends.
Prerequisites
- Node.js 18+ and npm installed
- An existing TypeScript MCP server project to instrument
- A MCPcat account and project ID (obtain at mcpcat.dev)
- Optional: API keys for Datadog, Sentry, PostHog, or an OTLP endpoint for telemetry export
Add the mcpcat package to your MCP server project
Install the MCPcat TypeScript SDK as a dependency in your existing MCP server project.
npm install -S mcpcatImport MCPcat and call track() on your server instance
In your MCP server entry point, import mcpcat and call track() with your server instance and your MCPcat project ID. This single call enables all telemetry collection.
import * as mcpcat from "mcpcat";
const mcpServer = new Server({ name: "my-mcp-server", version: "1.0.0" });
mcpcat.track(mcpServer, "proj_0000000");Optionally add user identification
Enrich telemetry with user context by providing an identify callback. This lets you correlate tool calls with specific users in the MCPcat dashboard.
mcpcat.track(mcpServer, "proj_0000000", {
identify: async (request, extra) => {
const user = await myapi.getUser(request.params.arguments.token);
return {
userId: user.id,
userName: user.name,
};
},
});Configure sensitive data redaction
If your tool calls handle PII or credentials, add a redactSensitiveInformation callback to scrub data before it is sent to MCPcat.
mcpcat.track(mcpServer, "proj_0000000", {
redactSensitiveInformation: async (text) => await redact(text),
});Deploy your instrumented server and view analytics
Deploy your MCP server as normal. MCPcat automatically collects tool call data, session flows, and performance metrics. Visit the MCPcat dashboard to view real-time analytics, session replays, and debug traces.
MCPcat Examples
Client configuration
Example Claude Desktop config for running an mcpcat-instrumented server built from source.
{
"mcpServers": {
"my-instrumented-server": {
"command": "node",
"args": ["/path/to/my-mcp-server/dist/index.js"]
}
}
}Minimal integration code
The minimal TypeScript code needed to add MCPcat tracking to any MCP server.
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import * as mcpcat from "mcpcat";
const server = new Server(
{ name: "echo-mcp", version: "0.1.0" },
{ capabilities: { tools: {} } }
);
// One line to enable full analytics
mcpcat.track(server, "proj_0000000");
// ... rest of your tool definitionsTroubleshooting MCPcat
track() call does not appear to send any data to MCPcat
Verify your project ID is correct (format: proj_XXXXXXX) and that your server has outbound internet access to reach the MCPcat collection endpoint. Check that mcpcat.track() is called before any tool handlers are registered.
TypeScript compilation errors after importing mcpcat
Ensure your tsconfig.json targets ES2020 or later and that moduleResolution is set to 'node16' or 'bundler'. Run 'npm install -S mcpcat' again to confirm the package is correctly installed with its type definitions.
Sensitive data appearing in MCPcat dashboard
Add a redactSensitiveInformation callback to the track() options that scrubs credentials, tokens, and PII from tool call arguments before telemetry is exported. Test the redaction function independently before deploying.
Frequently Asked Questions about MCPcat
What is MCPcat?
MCPcat is a Model Context Protocol (MCP) server that mcpcat is an analytics platform for mcp server owners π±. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install MCPcat?
Install via npm with the command: npx -y mcpcat. Then add the server configuration to your AI client's JSON config file (e.g., claude_desktop_config.json or .cursor/mcp.json).
Which AI clients work with MCPcat?
MCPcat works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is MCPcat free to use?
Yes, MCPcat is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
MCPcat Alternatives β Similar Analytics Servers
Looking for alternatives to MCPcat? Here are other popular analytics servers you can use with Claude, Cursor, and VS Code.
OpenMetadata
β 14.0kOpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team collaboration.
Superset
β 10.9kAn MCP server that provides AI assistants with full access to Apache Superset instances, enabling interaction with dashboards, charts, datasets, databases, and SQL execution capabilities.
Horizon
β 4.4kπ‘ Your own AI-powered news radar. Generates daily briefings in English & Chinese. | η¨ AI ζε»Ίδ½ δΈε±ηζ°ι»ι·θΎΎ
MCP Server Chart
β 4.1kEnables generation of 25+ types of charts and data visualizations using AntV, including bar charts, line charts, maps, mind maps, and specialized diagrams like fishbone and sankey charts. Supports both statistical charts and geographic visualizations
Muapi CLI
β 997Official CLI for muapi.ai β generate images, videos & audio from the terminal. MCP server, 14 AI models, npm + pip installable.
Weather MCP Server
β 907Weather Data Fetcher MCP server built with Node.js, MCP SDK, and Zod. Provides weather details like temperature and forecast for cities such as Noida and Delhi via a registered tool. Simplifies API integration, enabling structured responses for clien
Browse More Analytics MCP Servers
Explore all analytics servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.
Set Up MCPcat in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
Ready to use MCPcat?
Browse our complete directory of 33,000+ MCP servers, read setup guides for your editor, and start building with the Model Context Protocol.