Run Scout Monitoring's MCP tools locally with an API key: endpoints, traces, errors, N+1 insights.
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com.scoutapm/scout-mcp-local is an MCP server that run Scout Monitoring's MCP tools locally with an API key: endpoints, traces, errors, N+1 insights. Its tool list has not been published yet over stdio and http, requires no API key, and scores 84/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"scout-apm": {
"env": {
"SCOUT_API_KEY": "your_scout_api_key_here"
},
"args": [
"run",
"--rm",
"-i",
"--env",
"SCOUT_API_KEY",
"scoutapp/scout-mcp-local"
],
"command": "docker"
}
}
}Are you the author?
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Run Scout Monitoring's MCP tools locally with an API key: endpoints, traces, errors, N+1 insights.
This server supports HTTP transport. Be the first to test it - help the community know if it works.
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No known CVEs.
Checked @scout_apm/wizard against OSV.dev.
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This repository contains code to locally run an MCP server that can access Scout Monitoring data via Scout's API. We provide a Docker image that can be pulled and run by your AI Assistant to access Scout Monitoring data.
This puts Scout Monitoring's performance and error data directly in the hands of your AI Assistant. For Rails, Django, FastAPI, Laravel and more. Use it to get traces and errors with line-of-code information that the AI can use to target fixes right in your editor and codebase. N+1 queries, slow endpoints, slow queries, memory bloat, throughput issues - all your favorite performance problems surfaced and explained right where you are working.
If this makes your life a tiny bit better, why not :star: it?!
The simplest way to configure and start using the Scout MCP is with our interactive setup wizard. It handles all the prereqs and installation steps for you.
Run via npx:
npx @scout_apm/wizard
Build and run from source:
cd ./wizard
npm install
npm run build
node dist/wizard.js
The wizard will guide you through:
The wizard currently supports setup for:
For all others, it will output JSON that you can copy/paste into your AI Assistant's MCP configuration.
The Wizard is a great way to get started, but you can also set things up manually. You will need to have or create a Scout Monitoring account and obtain an API key.
The MCP server will not currently start without an API key set, either in the environment or by a command-line argument on startup.
We recommend using the provided Docker image to run the MCP server. It is intended to be started by your AI Assistant and configured with your Scout API key. Many local clients allow specifying a command to run the MCP server in some location. A few examples are provided below.
The Docker image is available on Docker Hub.
Of course, you can always clone this repo and run the MCP server directly; uv or other
environment management tools are recommended.
If you would like to configure the MCP manually, this usually just means supplying a command to run the MCP server with your API key in the environment to your AI Assistant's config. Here is the shape of the JSON (the top-level key varies):
{
"mcpServers": {
... [View full README on GitHub](https://github.com/scoutapp/scout-mcp-local#readme)