Scout 的本地 MCP 会直接将指标、跟踪和错误数据输入你的 AI 代理。对于那些能全方位完成的团队来说。
概览
该仓库包含代码，用于本地运行MCP服务器，通过Scout的API访问侦察监测数据。我们提供了一个Docker镜像，您的AI助手可以拉取并运行，以访问侦察监测数据。 这让Scout Monitoring的性能和错误数据直接交到你的AI助手手中。适用于Rails、Django、FastAPI、Laravel等。用它获取带有代码行信息的追踪和错误，AI可以利用这些信息直接在你的编辑器和代码库中定位修复。N+1查询、缓慢端点、缓慢查询、内存膨胀、吞吐量问题——你喜欢的所有性能问题都会在你工作现场显现并解释。 配置和开始使用 Scout MCP 最简单的方式是使用我们的交互式设置向导。它会帮你处理所有前置条件和安装步骤。
概述（AI 翻译）
克劳德密码
光标
确保在 SCOUT_API_KEY 中更新为你的实际 API 密钥
Arguments 在 MCP >光标设置中
VS Code 副驾驶
- VS Code 副驾驶文档
- 我们推荐“在您的工作区添加MCP服务器”选项
Claude Desktop
请在你的 claude 配置文件中添加以下内容：
- macOS：
~/Library/Application Support/Claude/claude_desktop_config.json - Windows：
%APPDATA%/Claude/claude_desktop_config.json
使用侦察监测MCP
Scout的MCP旨在将错误和性能数据直接交到…手中？你的AI助手手中。 用它获取带有代码行信息的痕迹和错误，AI可以利用这些信息来定位 在编辑器里就能修复。
大多数助手会同时展示原始工具调用并进行分析。桌面助理 可以轻松创建自定义JS应用程序，探索你想要的任何数据。 集成在代码编辑器中的助手可以使用轨迹数据和错误回溯来制作 修复方法就在你的代码库里。
将Scout的MCP与AI助手的其他工具结合起来：
- 基于错误和性能数据创建丰富的 GitHub/GitLab 问题
本页由 AI 翻译，技术细节请以原文为准。
README
以下为原文 README 节选，完整内容请查看原文。
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.
- Sign up
- Install the Scout Agent in your application and send Scout data!
- Visit settings to get or create an API key
- This is not your “Agent Key”; it’s the “API Key” that can be created on the Settings page
- This is a read-only key that can only access data in your account
- Install Docker. Instructions below assume you can start a Docker container
安装
docker run --rm -i --env SCOUT_API_KEY scoutapp/scout-mcp-local配置
{
"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"}
}
}
}