agentcathq/agentcat-typescript-sdk

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> [!NOTE]
> AgentCat v2 introduces compatibility with the MCP Protocol "Stateless" 2026-07-28 Update and the coinciding MCP TypeScript 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, Sentry, and PostHog.
bash
npm install agentcat
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.
context — a parameter asking the agent to explain, in one sentence, why it is making this call. This is where intent data comes from.