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AI agents are a new type of user. They scale like traditional software but act like humans. And existing analytics tools fail to give you the insights and data you need to optimize your products for agents. MCPcat in light mode MCPcat helps you:
  • Replay every session: step through exactly what your agents did and why they made each tool call
  • Understand agent goals: see what agents were trying to accomplish and whether they were successful
  • Automatically capture issues: track how often agents run into errors, hallucinations, and problems
  • Forward telemetry: send enriched data to your existing tools like Datadog, Sentry, and PostHog via OTEL
  • Get a high-level overview: visualize your traffic by client, server, location, model, and more

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What can MCPcat help with?

Session Replay

Replay agent sessions to debug issues and understand usage patterns

Agent Goals

Understand why agents call your tools

Identify Issues

Find the most common errors and hallucinations agents are making

Dashboard Analytics

Visualize usage trends, client distributions, and tool-level performance