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Add observability to Python MCP servers and monitor latency, errors, and usage.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Vigil" yet — see the docs or source repo.
Show me how to instrument a Python FastMCP service with Vigil and explain how to view per-tool p50, p95, p99 latency, error rate, and call volume.
Setup steps or sample code plus guidance for viewing key per-tool performance metrics.
I suspect an MCP tool often returns empty values without throwing errors. Explain how to use Vigil to detect silent failures like empty/null returns and isError, and suggest debugging steps.
Methods to monitor silent failures, along with analysis and debugging suggestions for abnormal returns.
Give me a plan for using Vigil's REST API, CLI, and alert hooks to notify the team automatically when an MCP tool's error rate rises or p95 latency exceeds a threshold.
An operations plan example including alert conditions, invocation methods, and notification flow.
Mount an MCP server to FastAPI for runtime route and schema inspection.
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Build secure, observable MCP servers with a production-ready starter foundation.
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