Open-source, self-hosted analytics for MCP servers
View on GitHub ↗Open-source, self-hosted analytics for MCP servers. See which tools, resources and prompts get used, by which client, how fast they answer, and why they fail.
Add one line to your MCP server, run the dashboard with docker compose up, and nothing ever leaves your machine.
- Every call, from every client. Tool calls, resource reads and prompt gets, with the client that made them: Claude, Claude Code, Cursor, ChatGPT and the rest. - Response times that mean something. Median and 95th percentile per tool, and the full distribution, so a cache hit and a slow path do not hide inside one average. - Answer sizes. How large each tool's answers are, typical and largest: a tool that now and then returns megabytes fills the agent's context while looking fine on every latency chart. - Failures, told apart. A handler that threw, a tool that answered with an error, arguments the server refused, and tools that agents asked for but your server does not have: which clients asked, the closest name you do have, and what the agent did next. - Sessions. Each connection's calls, step by step, as the agent made them. - Releases. Every call carries the version of your server that answered it; the charts mark where each release began and compare it with the one before. - Alerts to Slack, Discord or any webhook, when errors climb or a server goes quiet, for a whole server or one tool. - Your data, yours to take. CSV and NDJSON exports of anything you can see, and forwarding to OpenTelemetry for Grafana, Datadog, Honeycomb and the like. - Private by design. Parameter values never leave your server's
From the project README.
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Every visit, truly told. Self-hosted web analytics from your server access log: see people, AI assistants (ChatGPT, Claude, Perplexity), crawlers and bots that JavaScript analytics miss. Every figure
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