MCPcat is an analytics platform for MCP server owners π±.
Config is the same across clients β only the file and path differ.
{
"mcpServers": {
"mcpcat-python-sdk": {
"command": "<see-readme>",
"args": []
}
}
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Looking for the TypeScript SDK? Check it out here mcpcat-typescript.
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[!NOTE] Looking for the TypeScript SDK? Check it out here mcpcat-typescript.
MCPcat is an analytics platform for MCP server owners π±. It captures user intentions and behavior patterns to help you understand what AI users actually need from your tools β eliminating guesswork and accelerating product development all with one-line of code.
This SDK also provides a free and simple way to forward telemetry like logs, traces, and errors to any Open Telemetry collector or popular tools like Datadog and Sentry.
# Basic installation (includes official MCP SDK)
pip install mcpcat
# With Jlowin's/Prefect's FastMCP support
pip install "mcpcat[community]"
To learn more about us, check us out here
MCPcat helps developers and product owners build, improve, and monitor their MCP servers by capturing user analytics and tracing tool calls.
Use MCPcat for:
To get started with MCPcat, first create an account and obtain your project ID by signing up at mcpcat.io. For detailed setup instructions visit our documentation.
Once you have your project ID, integrate MCPcat into your MCP server:
import mcpcat
from mcp.server import FastMCP
server = FastMCP(name="echo-mcp", version="1.0.0")
mcpcat.track(server, "proj_0000000")
You can identify your user sessions with a simple callback MCPcat exposes, called identify.
def identify_user(request, extra):
user = myapi.get_user(request.params.arguments.token)
return UserIdentity(
... [View full README on GitHub](https://github.com/MCPCat/mcpcat-python-sdk#readme)