AI Skill Hub 推荐使用:MCP分析服务器 是一款优质的MCP工具。AI 综合评分 7.5 分,在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案,这是一个值得深入了解的选择。
MCP分析服务器 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
MCP分析服务器 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/tosin2013/mcp-adr-analysis-server
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"mcp-----": {
"command": "npx",
"args": ["-y", "mcp-adr-analysis-server"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 MCP分析服务器 执行以下任务... Claude: [自动调用 MCP分析服务器 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"mcp_____": {
"command": "npx",
"args": ["-y", "mcp-adr-analysis-server"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
AI-powered architectural analysis for intelligent development workflows. Returns actual analysis results, not prompts to submit elsewhere.
🤖 AI-Powered Analysis - Immediate architectural insights with OpenRouter.ai integration 🏗️ Technology Detection - Identify any tech stack and architectural patterns 📋 ADR Management - Generate, suggest, and maintain Architectural Decision Records 🔗 Smart Code Linking - AI-powered discovery of code files related to ADRs and decisions 🛡️ Security & Compliance - Detect and mask sensitive content automatically 🧪 TDD Integration - Two-phase Test-Driven Development with validation 🚀 Deployment Readiness - Zero-tolerance test validation with hard blocking
📖 View Full Capabilities → · 📜 Release policy → · 🗒️ Changelog →
Before installing, verify you have:
node --version # Should show v20.0.0 or higher
npm --version # Should show 9.0.0 or higher (included with Node.js 20+)
Required:
npm install for native module compilation (tree-sitter incremental code parsers for YAML and TypeScript)HTTP_PROXY and HTTPS_PROXY environment variables```bash
npm install -g mcp-adr-analysis-server
npx mcp-adr-analysis-server
curl -sSL https://raw.githubusercontent.com/tosin2013/mcp-adr-analysis-server/main/scripts/install-rhel.sh | bash ```
Note: When installing from source,npm run buildis required before running the server since thebinentry points to./dist/src/index.js.
OPENROUTER_API_KEY=your_key + EXECUTION_MODE=full{
"mcpServers": {
"adr-analysis": {
"command": "mcp-adr-analysis-server",
"env": {
"PROJECT_PATH": "/path/to/your/project",
"OPENROUTER_API_KEY": "your_key_here",
"EXECUTION_MODE": "full"
}
}
}
}
Claude Desktop users: Save this JSON to~/Library/Application Support/Claude/claude_desktop_config.json(macOS) or%APPDATA%\Claude\claude_desktop_config.json(Windows).
<details> <summary><b>Config locations for other clients</b></summary>
| Client | Config file location |
|---|---|
| **Claude Desktop (macOS)** | ~/Library/Application Support/Claude/claude_desktop_config.json |
| **Claude Desktop (Windows)** | %APPDATA%\Claude\claude_desktop_config.json |
| **Cline (VS Code)** | VS Code Settings → Cline → MCP Servers (or .vscode/cline_mcp_settings.json) |
| **Cursor** | Cursor Settings → MCP → Add Server |
</details>
<details> <summary><b>With ADR Aggregator (Optional)</b></summary>
{
"mcpServers": {
"adr-analysis": {
"command": "mcp-adr-analysis-server",
"env": {
"PROJECT_PATH": "/path/to/your/project",
"OPENROUTER_API_KEY": "your_key_here",
"EXECUTION_MODE": "full",
"ADR_AGGREGATOR_API_KEY": "agg_your_key_here"
}
}
}
}
Get your API key at adraggregator.com
</details>
Enhanced web research capabilities for comprehensive architectural analysis.
Note: You don't need Firecrawl for basic ADR analysis. The server works fully without it. Only configure Firecrawl if you need web research features like the perform_research tool with external sources.
<details> <summary><b>When is Firecrawl useful?</b></summary>
</details>
```bash
Just ask your MCP client in natural language — no code required:
"Analyze this React project's architecture and suggest ADRs for any implicit decisions"
"Generate ADRs from the PRD.md file and create a todo.md with implementation tasks"
"Check this codebase for security issues and provide masking recommendations"
The server returns actual analysis results instead of prompts to submit elsewhere!
<details> <summary><b>Programmatic Usage (Advanced)</b></summary>
If you're integrating the server into your own tooling via the MCP SDK:
// Basic project analysis
const analysis = await analyzeProjectEcosystem({
projectPath: '/path/to/project',
analysisType: 'comprehensive',
});
// Generate ADRs from requirements
const adrs = await generateAdrsFromPrd({
prdPath: 'docs/PRD.md',
outputDirectory: 'docs/adrs',
});
// Smart Code Linking - Find code related to ADR decisions
const relatedCode = await findRelatedCode(
'docs/adrs/001-auth-system.md',
'We will implement JWT authentication with Express middleware',
'/path/to/project',
{
useAI: true, // AI-powered keyword extraction
useRipgrep: true, // Fast text search
maxFiles: 10, // Limit results
includeContent: true, // Include file contents
}
);
</details>
📖 Complete Usage Guide → | API Reference →
Try it out: This repo includes asample-project/directory with example ADRs and source code. PointPROJECT_PATHat it to experiment without affecting your own codebase. Note: The sample project is only available when cloning from source (Option 3 above). If you installed via npm (Option 1 or 2), create your own test project or clone the repo separately to access the sample:git clone --depth 1 https://github.com/tosin2013/mcp-adr-analysis-server.git sample-test
👨💻 AI Coding Assistants - Enhance Claude, Cline, Cursor with architectural intelligence 💬 Conversational AI - Answer architecture questions with confidence scoring 🤖 Autonomous Agents - Continuous analysis and rule enforcement 🏢 Enterprise Teams - Portfolio analysis and migration planning
git clone https://github.com/YOUR_USERNAME/mcp-adr-analysis-server.gitgit checkout -b feature/your-feature-namenpm test (maintain >80% coverage)git clone https://github.com/tosin2013/mcp-adr-analysis-server.git cd mcp-adr-analysis-server && npm install && npm run build
export FIRECRAWL_ENABLED="true" export FIRECRAWL_API_KEY="fc-your-api-key-here"
export FIRECRAWL_ENABLED="true" export FIRECRAWL_BASE_URL="http://localhost:3000"
```
ADR Aggregator is a platform for cross-team ADR visibility and governance. It provides:
Note: ADR Aggregator is optional. All core analysis features work without it.
```bash
sync_to_aggregator(full_sync: true) ```
Benefits: Cross-team visibility • Staleness alerts • Compliance tracking • Organization-wide knowledge graph
export ADR_AGGREGATOR_API_KEY="agg_your_key_here" ```
```bash
Common Issues:
EXECUTION_MODE=full + API keynpm install && npm run buildmcp-adr-analysis-server 是一个基于 MCP (Model Context Protocol) 标准构建的强大工具,专门用于架构决策记录 (ADR) 的自动化分析。它能够通过集成 OpenRouter.ai 提供智能化的架构洞察,帮助开发者在复杂的代码库中维护、生成并管理架构决策,确保技术决策的可追溯性与一致性。
该项目具备多项核心 AI 能力:通过 OpenRouter.ai 实现 AI 驱动的架构分析;能够自��识别技术栈与架构模式;支持 ADR 的自动生成、建议与维护;具备智能代码链接功能,可将 ADR 与相关代码文件精准关联;此外,还内置了安全与合规性检测功能,帮助开发者及时发现潜在风险。
在安装之前,请确保您的环境已安装 Node.js v20.0.0 或更高版本,以及 npm 9.0.0 或更高版本。由于项目在安装过程中需要通过 npm 下载并编译 tree-sitter 原生模块(用于解析 YAML 和 TypeScript),因此必须确保网络环境可以访问互联网。若处于企业内网环境,请务必正确配置 HTTP_PROXY 和 HTTPS_PROXY 环境变量。
您可以根据使用场景选择不同的安装方式:1. 全局安装(推荐频繁使用):使用 `npm install -g mcp-adr-analysis-server`;2. 免安装运行:直接使用 `npx mcp-adr-analysis-server`;3. 源码构建(适用于开发或自定义):通过 git clone 项目仓库后,执行 `npm install` 和 `npm run build` 进行编译。
本项目支持通过自然语言与 MCP 客户端(如 Claude、Cline、Cursor 等)进行交互,无需编写代码。您可以直接询问:“分析这个 React 项目的架构并为隐式决策建议 ADR” 或 “根据 PRD.md 生成 ADR 并创建实现任务清单”。对于开��者而言,它不仅是 AI 编程助手的增强插件,也能作为自主 Agent 进行持续的架构规则检查。
项目支持多种配置模式以适应不同环境。对于云服务集成,可以通过设置 `FIRECRAWL_ENABLED="true"` 并配置相应的 `FIRECRAWL_API_KEY` 来启用;若采用自托管模式,则需配置 `FIRECRAWL_BASE_URL`。此外,若需使用 ADR Aggregator 服务,请务必通过环境变量设置 `ADR_AGGREGATOR_API_KEY`。
本项目通过环境变量管理关键的 API 密钥。开发者需要前往 adraggregator.com 获取专属的 API Key,并通过 `export ADR_AGGREGATOR_API_KEY="your_key_here"` 的方式进行配置,以确保分析功能与数据聚合服务的正常通信。
对于新仓库的使用流程,本项目旨在通过 AI 自动识别项目结构并建立架构文档。通过集成到开发工作流中,它可以实现从需求文档 (PRD) 到架构决策 (ADR) 再到任务清单 (todo.md) 的自动化转化,确保代码实现与架构设计保持高度同步。
针对常见问题,RHEL 系统用户建议使用专门的安装脚本;若遇到工具仅返回提示词而非结果的情况,请尝试设置 `EXECUTION_MODE=full` 并配置 API Key;若出现模块缺失错误,请重新执行 `npm install && npm run build`;对于权限问题,请重点检查文件权限与项目路径设置。
高质量的MCP分析服务器,具有较强的实用价值
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
总体来看,MCP分析服务器 是一款质量良好的MCP工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | mcp-adr-analysis-server |
| 原始描述 | 开源MCP工具:A sophisticated Model Context Protocol (MCP) server for analyzing Architectural 。⭐28 · TypeScript |
| Topics | mcpadrai-agentsarchitectural-decision-records |
| GitHub | https://github.com/tosin2013/mcp-adr-analysis-server |
| License | MIT |
| 语言 | TypeScript |
收录时间:2026-05-25 · 更新时间:2026-05-26 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端