This MCP server allows local access to Scout Monitoring data via Scout's API, enabling AI assistants to retrieve performance and error data for various frameworks. It provides tools to analyze application metrics and insights directly in the development environment.
From the registry: An MCP server for Scout Monitoring data interactions.
Please install the `scout-mcp-local` MCP server into my current AI client (that's you).
Required prerequisites (do these first if not already done):
- **Docker** — Required to run the Docker image (recommended method). (https://docs.docker.com/get-docker/)
- **Scout APM API Key** — Active Scout Monitoring account with API key from settings page. (https://scoutapm.com/settings)
Canonical MCP server config (stdio transport):
- command: `docker`
- args: ["run","--rm","-i","--env","SCOUT_API_KEY","scoutapp/scout-mcp-local"]
- required environment variables:
- `SCOUT_API_KEY`: Scout APM API key (read-only) from Settings page. Not the Agent Key. (example: `your_scout_api_key_here`)
Note: Scout APM performance monitoring: traces, errors, N+1 queries, slow endpoints. Use npx @scout_apm/wizard for guided setup. 8 tools for performance data access.
Add this MCP server to my current client's config in the correct format for you. If you need secrets or credentials I haven't provided, ASK me — do not invent values or leave raw placeholders. After adding it, tell me how to verify the server is connected.SCOUT_API_KEYrequiredAPI key required to access Scout Monitoring data.Real-time Kubernetes network traffic visibility and API analysis for HTTP, gRPC, Redis, Kafka, DNS.