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    Mcp Adr Analysis Server

    A sophisticated Model Context Protocol (MCP) server for analyzing Architectural Decision Records (ADRs) and providing deep architectural insights to AI agents.

    10 stars
    TypeScript
    Updated Oct 16, 2025
    adr
    architectural-decision-records
    mcp-server

    Table of Contents

    • What is MCP?
    • TL;DR
    • ✨ Core Capabilities
    • Prerequisites
    • Network Requirements
    • 📦 Quick Installation
    • ⚡ Quick Setup (3 Steps)
    • Execution Modes
    • 🚀 Usage Examples
    • 🎯 Use Cases
    • 🛠️ Technology Stack
    • 📁 Project Structure
    • 🧪 Testing
    • 🔥 Firecrawl Integration (Optional — Skip for Getting Started)
    • 🌐 ADR Aggregator Integration (Optional)
    • Available Tools
    • Workflow for New Repos
    • 🔧 Development
    • Viewing Documentation Locally
    • 🔧 Troubleshooting
    • 🔒 Security & Performance
    • 🔐 Security Vulnerability Reporting
    • 🤝 Contributing
    • 🌟 Quick Start for Contributors
    • 👶 First Time Contributing?
    • 📝 Reporting Issues
    • 🔗 Resources
    • 📄 License
    • 🙏 Acknowledgments

    Table of Contents

    • What is MCP?
    • TL;DR
    • ✨ Core Capabilities
    • Prerequisites
    • Network Requirements
    • 📦 Quick Installation
    • ⚡ Quick Setup (3 Steps)
    • Execution Modes
    • 🚀 Usage Examples
    • 🎯 Use Cases
    • 🛠️ Technology Stack
    • 📁 Project Structure
    • 🧪 Testing
    • 🔥 Firecrawl Integration (Optional — Skip for Getting Started)
    • 🌐 ADR Aggregator Integration (Optional)
    • Available Tools
    • Workflow for New Repos
    • 🔧 Development
    • Viewing Documentation Locally
    • 🔧 Troubleshooting
    • 🔒 Security & Performance
    • 🔐 Security Vulnerability Reporting
    • 🤝 Contributing
    • 🌟 Quick Start for Contributors
    • 👶 First Time Contributing?
    • 📝 Reporting Issues
    • 🔗 Resources
    • 📄 License
    • 🙏 Acknowledgments

    Documentation

    MCP (Model Context Protocol) ADR (Architectural Decision Record) Analysis Server

    GitHub

    License

    NPM Version

    Node.js

    TypeScript

    Good First Issues

    AI-powered architectural analysis for intelligent development workflows. Returns actual analysis results, not prompts to submit elsewhere.

    What is MCP?

    The Model Context Protocol (MCP) is an open standard that enables seamless integration between AI assistants and external tools and data sources. Think of it as a universal adapter that lets AI assistants like Claude, Cline, and Cursor connect to specialized analysis servers. This server enhances AI assistants with deep architectural analysis capabilities, enabling intelligent code generation, decision tracking, and development workflow automation.

    TL;DR

    What: MCP server that provides AI-powered architectural decision analysis and ADR management

    Who: AI coding assistants (Claude, Cline, Cursor), enterprise architects, development teams

    Why: Get immediate architectural insights instead of prompts, with 95% confidence scoring

    How: npm install -g mcp-adr-analysis-server → Configure with OpenRouter API → Start analyzing

    Key Features: Tree-sitter AST analysis • Security content masking • Test-driven development • Deployment readiness validation

    Key Terms

    TermDefinition
    ADRArchitectural Decision Record — A document that captures an important architectural decision along with its context, alternatives considered, and consequences.
    MCPModel Context Protocol — An open standard enabling AI assistants to connect to external tools and data sources.
    Tree-sitterAn incremental parsing library that provides AST (Abstract Syntax Tree) analysis for 50+ languages. Used for semantic code understanding, extracting function signatures, and identifying architectural patterns.
    Knowledge GraphA graph database maintained by the server that tracks relationships between ADRs, code implementations, and architectural decisions. Enables intelligent code linking and impact analysis.
    Smart Code LinkingAI-powered discovery of code files related to ADRs and architectural decisions, using keyword extraction and semantic search.

    ---

    Author: Tosin Akinosho | Repository: GitHub

    ✨ Core Capabilities

    🤖 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 →**

    Prerequisites

    Before installing, verify you have:

    bash
    node --version  # Should show v20.0.0 or higher
    npm --version   # Should show 9.0.0 or higher (included with Node.js 20+)

    Required:

    • Node.js 20.0.0 or higher — Download or use nvm/fnm
    • npm 9.0.0 or higher (included with Node.js 20+)
    • An MCP-compatible client — Claude Desktop, Cline, Cursor, or Windsurf

    Network Requirements

    • Internet access required during npm install for native module compilation (tree-sitter-yaml, tree-sitter-typescript)
    • If behind a corporate proxy, set HTTP_PROXY and HTTPS_PROXY environment variables
    • Offline fallback: If native builds fail, the server operates in reduced mode without tree-sitter code analysis

    📦 Quick Installation

    bash
    # Option 1: Global installation (recommended for frequent use)
    npm install -g mcp-adr-analysis-server
    
    # Option 2: Use npx (no installation required)
    npx mcp-adr-analysis-server
    
    # Option 3: From source (for development or customization)
    git clone https://github.com/tosin2013/mcp-adr-analysis-server.git
    cd mcp-adr-analysis-server && npm install && npm run build
    
    # Option 4: RHEL 9/10 systems (special installer)
    curl -sSL https://raw.githubusercontent.com/tosin2013/mcp-adr-analysis-server/main/scripts/install-rhel.sh | bash

    Note: When installing from source, npm run build is required before running the server since the bin entry points to ./dist/src/index.js.

    📖 **Detailed Installation Guide → | RHEL Setup →**

    ⚡ Quick Setup (3 Steps)

    1. Get API Key: Sign up at OpenRouter.ai/keys — OpenRouter is an API gateway that provides access to multiple AI models (Claude, GPT, etc.) through a single key. _No API key? The server still works in prompt-only mode — see Execution Modes below._

    2. Set Environment: OPENROUTER_API_KEY=your_key + EXECUTION_MODE=full

    3. Configure Client: Add to Claude Desktop, Cline, Cursor, or Windsurf

    json
    {
      "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).

    Config locations for other clients

    ClientConfig 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)
    CursorCursor Settings → MCP → Add Server

    With ADR Aggregator (Optional)

    json
    {
      "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

    📖 **Full Configuration Guide → | Client Setup →**

    Execution Modes

    Full ModePrompt-Only Mode
    Requires API key?Yes (OPENROUTER_API_KEY)No
    ReturnsActual analysis results with confidence scoresPrompts you can paste into any AI chat
    Set viaEXECUTION_MODE=fullEXECUTION_MODE=prompt-only (default)
    Best forProduction use, automationTrying it out, no-cost exploration
    Available FeaturesAll 73 tools, AI analysis, confidence scoring, Smart Code Linking, Knowledge GraphAnalysis prompts, templates, local file operations, ADR discovery
    Unavailable Features—AI execution, confidence scores, Smart Code Linking, web research

    Tip: Start with prompt-only mode to explore the tool catalog — you can analyze projects, discover ADRs, and generate templates without an API key. Add an API key when you're ready for AI-powered analysis with confidence scoring.

    🚀 Usage Examples

    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!

    Programmatic Usage (Advanced)

    If you're integrating the server into your own tooling via the MCP SDK:

    typescript
    // 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
      }
    );

    📖 **Complete Usage Guide → | API Reference →**

    Try it out: This repo includes a [sample-project/](sample-project/) directory with example ADRs and source code. Point PROJECT_PATH at 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

    🎯 Use Cases

    👨‍💻 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

    📖 **Detailed Use Cases →**

    🛠️ Technology Stack

    Runtime: Node.js 20+ • Language: TypeScript • Framework: MCP SDK • Testing: Jest (>80% coverage)

    Search: ripgrep (fast text search) + fast-glob (file matching) • AI Integration: OpenRouter.ai • Web Research: Firecrawl • Code Analysis: tree-sitter (code parser) + Smart Code Linking

    📖 **Technical Details →**

    📁 Project Structure

    code
    src/tools/     # 73 MCP tools for analysis
    docs/adrs/     # Architectural Decision Records
    tests/         # >80% test coverage
    .github/       # CI/CD automation

    📖 **Full Structure →**

    🧪 Testing

    bash
    npm test              # Run all tests (>80% coverage)
    npm run test:coverage # Coverage report

    📖 **Testing Guide →**

    🔥 Firecrawl Integration (Optional — Skip for Getting Started)

    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.

    When is Firecrawl useful?

    • ADR research — automatically pull best practices from official docs when generating ADRs
    • Technology evaluation — compare frameworks by crawling their documentation and changelogs
    • Security audits — check CVE databases and security advisories for your dependencies
    • Migration planning — gather migration guides and breaking-change notes from upstream projects
    bash
    # Option 1: Cloud service (recommended)
    export FIRECRAWL_ENABLED="true"
    export FIRECRAWL_API_KEY="fc-your-api-key-here"
    
    # Option 2: Self-hosted
    export FIRECRAWL_ENABLED="true"
    export FIRECRAWL_BASE_URL="http://localhost:3000"
    
    # Option 3: Disabled (default - server works without web search)

    📖 **Firecrawl Setup Guide →**

    🌐 ADR Aggregator Integration (Optional)

    ADR Aggregator is a platform for cross-team ADR visibility and governance. It provides:

    • Cross-repository knowledge graphs — See how architectural decisions relate across projects
    • Governance dashboards — Track ADR compliance, staleness, and review cycles
    • Template library — Access domain-specific ADR templates (security, API, database, etc.)
    • Team collaboration — Share architectural decisions organization-wide

    Note: ADR Aggregator is optional. All core analysis features work without it.

    bash
    # Set your API key (get one at adraggregator.com)
    export ADR_AGGREGATOR_API_KEY="agg_your_key_here"

    Available Tools

    ToolDescriptionFreePro+Team
    sync_to_aggregatorPush local ADRs to platform✅✅✅
    get_adr_contextPull ADR context from platform✅✅✅
    get_staleness_reportGet ADR governance/health reports✅✅✅
    get_adr_templatesRetrieve domain-specific templates✅✅✅
    get_adr_diagramsGet Mermaid diagrams for ADRs—✅✅
    validate_adr_complianceValidate ADR implementation—✅✅
    get_knowledge_graphCross-repository knowledge graph——✅

    Workflow for New Repos

    bash
    # 1. Analyze codebase for implicit architectural decisions
    suggest_adrs(analysisType: 'implicit_decisions')
    
    # 2. Generate ADR files from suggestions
    generate_adr_from_decision(decisionData)
    
    # 3. Save ADRs to docs/adrs/
    
    # 4. (Optional) Sync to adraggregator.com
    sync_to_aggregator(full_sync: true)

    Benefits: Cross-team visibility • Staleness alerts • Compliance tracking • Organization-wide knowledge graph

    📖 **ADR Aggregator Guide → | 📖 MCP Integration Guide →**

    🔧 Development

    bash
    git clone https://github.com/tosin2013/mcp-adr-analysis-server.git
    cd mcp-adr-analysis-server
    npm install && npm run build && npm test

    Quality Standards: TypeScript strict mode • ESLint • >80% test coverage • Pre-commit hooks

    Viewing Documentation Locally

    The documentation site is built with Docusaurus:

    bash
    cd docs
    npm install
    npm run build
    npm run serve

    Then open http://localhost:3000/mcp-adr-analysis-server/ in your browser.

    📖 **Development Guide → | Contributing →**

    🔧 Troubleshooting

    Common Issues:

    • RHEL Systems: Use special installer script
    • Tools return prompts: Set EXECUTION_MODE=full + API key
    • Module not found: Run npm install && npm run build
    • Permission denied: Check file permissions and project path

    📖 **Complete Troubleshooting Guide →**

    🔒 Security & Performance

    Security: Automatic secret detection • Content masking • Local processing • Zero trust

    Performance: Multi-level caching • Incremental analysis • Parallel processing • Memory optimization

    📖 **Security Guide → | Performance →**

    🔐 Security Vulnerability Reporting

    Found a security issue? Please read our Security Policy for responsible disclosure procedures. Do not create public issues for security vulnerabilities.

    🤝 Contributing

    We welcome contributions! Whether you're fixing bugs, adding features, or improving documentation, your help is appreciated.

    🌟 Quick Start for Contributors

    1. Fork the repository

    2. Clone your fork: git clone https://github.com/YOUR_USERNAME/mcp-adr-analysis-server.git

    3. Create a branch: git checkout -b feature/your-feature-name

    4. Make your changes with tests

    5. Test: npm test (maintain >80% coverage)

    6. Submit a Pull Request

    👶 First Time Contributing?

    Looking for a good first issue? Check out our **good first issues** - these are beginner-friendly tasks perfect for getting started!

    New to open source? Our Contributing Guide walks you through the entire process step-by-step.

    📝 Reporting Issues

    Use our **issue templates** when reporting bugs or requesting features. Templates help us understand and resolve issues faster.

    Standards: TypeScript strict • >80% coverage • ESLint • Security validation • MCP compliance

    📖 **Full Contributing Guide → | Code of Conduct →**

    🔗 Resources

    Official: MCP Specification • MCP SDK

    Community: MCP Registry • Discord

    Project: ADRs • Progress • Publishing Guide

    📄 License

    MIT License - see LICENSE file for details.

    🙏 Acknowledgments

    • Anthropic for creating the Model Context Protocol
    • The MCP Community for inspiration and best practices
    • Contributors who help make this project better

    ---

    **Built with ❤️ by Tosin Akinosho for AI-driven architectural analysis**

    _Empowering AI assistants with deep architectural intelligence and decision-making capabilities._

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