> ## Documentation Index > Fetch the complete documentation index at: https://docs.mcpcat.io/llms.txt > Use this file to discover all available pages before exploring further. # Introduction > MCPcat tells you exactly what agents are doing on your product and where they're getting stuck. **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 ## What can MCPcat help with? Replay agent sessions to debug issues and understand usage patterns Understand *why* agents call your tools Find the most common errors and hallucinations agents are making Visualize usage trends, client distributions, and tool-level performance