Scout Monitoring (local) MCP server

Scout Monitoring MCP

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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?!

Setup Wizard

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:

• Selecting your AI coding platform (Cursor, Claude Code, Claude Desktop)
• Entering your Scout API key
• Automatically configuring the MCP server settings

Supported Platforms

The wizard currently supports setup for:

• Cursor - Automatically configures MCP settings
• Claude Code (CLI) - Provides the correct command to run
• Claude Desktop - Updates the configuration file for Windows/Mac

For all others, it will output JSON that you can copy/paste into your AI Assistant's MCP configuration.

Prerequisites

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.

up](https://scoutapm.com/users/signup?utmsource=github&utmmedium=github&utmcampaign=scout-mcp-local)

1. [Sign

1. Install the Scout Agent in your application and send Scout data!

are set in your config for the best experience

• Ruby
• Python
• PHP
• If you are trying this out locally, make sure monitor: true, errors_enabled: true

1. Visit settings to get or create an API key

Settings page

• This is not your "Agent Key"; it's the "API Key" that can be created on the

• This is a read-only key that can only access data in your account

1. Install Docker. Instructions below assume you can start a Docker container

The MCP server will not currently start without an API key set, either in the environment or by a command-line argument on startup.

Installation

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.

Configure a local Client (e.g. Claude/Cursor/VS Code Copilot)

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):

Shortened. The full README is on GitHub.