agentcathq/agentcat-python-sdk

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> [!NOTE]
> AgentCat v2 introduces compatibility with the MCP Protocol "Stateless" 2026-07-28 Update and the coinciding MCP Python SDK v2 release that puts it into effect. The stateless transition has a massive impact on analytics, as sessions were a built-in concept tying related tool calls together. AgentCat has now migrated its session tracking under guidance of the MCP core team's recommendations of using explicit handles (SEP-2567).
> As a result AgentCat now injects a sessionid on every MCP tool call to associate them under the same task umbrella. Our evals show much higher tool correlation accuracy at the cost of [!IMPORTANT]
> MCPcat is now AgentCat 🐱 — same team, same product, new name. This package was previously published as mcpcat, which keeps working forever, but new features land here. Upgrading takes a few minutes — see the migration guide.
AgentCat is an analytics platform for MCP server owners 🐱. It captures user intentions and behavior patterns to help you understand what AI users actually need from your tools — 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.
bash
# Basic installation (includes official MCP SDK)
pip install agentcat
# With community FastMCP support
pip install "agentcat[community]"
To learn more about us, check us out here. For detailed guides visit our documentation.
## Why use AgentCat? 🤔
AgentCat helps builders of MCP servers, Claude Connectors, and ChatGPT Plugins learn how to improve them by capturing any agents goals and detecting when they get stuck.
Use AgentCat for:
Agent session replay 🎬. Follow alongside your users and their agents to understand why they're using your MCP servers, what functionality you're missing, and what clients they're coming from.
Trace debugging 🔍. See where your users are getting stuck, track and find when LLMs get confused by your API, and debug sessions across all deployments of your MCP server.
Existing platform support 📊. Get logging and tracing out of the box for your existing observability platforms (OpenTelemetry, Datadog, Sentry) — eliminating the tedious work of implementing telemetry yourself.
## How it works
AgentCat works as a lightweight middleware inside your MCP server. When you call track(), it seamlessly modifies your registered tool schemas in place, following the MCP core team's explicit handles (SEP-2567) guidelines. Concretely, AgentCat adds the following to your server:
sessionid — a parameter injected into each tool's input schema. Agents echo it back on every call, letting AgentCat group related tool calls into one task even over stateless transports. Values are validated: anything AgentCat did not issue is rejected rather than adopted, and the agent is told to re-send the ID it was given.
agentid (off by default) — enabled with enableagenttracking=True. Each agent self-generates its own ID, keeping parallel agents working the same task individually attributable.