Scout Monitoring MCP
Scout's official MCP pipes error, trace and metric data from production to your AI agent
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Overview
This repository contains code to locally run an MCP server that can access [Scout Monitoring](https://www.scoutapm.com) 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.
Installation
npx @scout_apm/wizard
Configuration
{
"mcpServers": {
"scout-apm": {
"command": "docker",
"args": ["run", "--rm", "-i", "--env", "SCOUT_API_KEY", "scoutapp/scout-mcp-local"],
"env": { "SCOUT_API_KEY": "your_scout_api_key_here"}
}Capabilities
- List your Scout applications
Ask the assistant to retrieve all monitored apps with `list_apps`, optionally filtering by recent activity.
- Identify slow endpoints
Use `get_app_endpoints` and `get_endpoint_metrics` to surface endpoints with high response times or throughput issues.
- Inspect individual traces
Pull a specific trace via `get_app_trace` to examine span-level execution details and backtrace data.
- Review recent error groups
Fetch error groups with `get_app_error_groups` and examine backtraces to suggest targeted code fixes.
- Surface performance insights
Retrieve N+1 query detections, memory bloat, and slow query warnings using `get_app_insights`.
Tags
- monitoring
- observability-incident
- devops
- performance
- data-analysis
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