Hey everyone!

We've been working with several MCP server maintainers and we noticed some difficulties getting drop-in logging and identity attribution working out of the box with existing vendors. A couple of challenges we hoped to solve were: - Baseline piping of tool calls to traditional vendors - How to tie tool calls to a “user session” - Understanding the context behind tool calls made by agents

So we built something. :) The MCPcat library is completely free to use, MIT licensed, and provides a one-line solution for adding logging and observability to any vendor that supports OpenTelemetry. We added custom support for Datadog and Sentry because we personally use those vendors, but we’re happy to add more if there’s interest.

Here’s how it works:

  mcpcat.track(serverObject, {...options…})

This initializes a series of listeners that: 1. Categorize events within the same working session 2. Publish those events directly to your third-party data provider

Optionally, you can redact sensitive data. The data never touches our servers (unless you opt in to additional contextual analysis, which I mention below).

Some teams might also want a better understanding of “what use cases are people finding with my MCP server.” For that, we provide a separate dashboard that visualizes the user journey in more detail (free for a high baseline of monthly usage and always free for open source projects).

We have two SDKs so far: Python SDK: <https://github.com/MCPCat/mcpcat-python-sdk> TypeScript SDK: <https://github.com/MCPCat/mcpcat-typescript-sdk>

Other SDKs are on the way!