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MCP Adr Analysis Server

作者:tosin2013版本 2.14.19i★ –i在你的电脑上运行
注册名称io.github.tosin2013/mcp-adr-analysis-server

安装

概览

作者提供的说明(英文原文)

ADR drift detection, content safety, and decision memory for architectural decisions

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆
  • 你需要填写:OPENROUTER_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: PROJECT_PATH, OPENROUTER_API_KEY, EXECUTION_MODE, ADR_DIRECTORY

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "adr-analysis": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-adr-analysis-server"
      ],
      "env": {
        "PROJECT_PATH": "your-value",
        "OPENROUTER_API_KEY": "your-value",
        "EXECUTION_MODE": "your-value",
        "ADR_DIRECTORY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add adr-analysis --env PROJECT_PATH=your-value --env OPENROUTER_API_KEY=your-value --env EXECUTION_MODE=your-value --env ADR_DIRECTORY=your-value -- npx -y mcp-adr-analysis-server

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "adr-analysis": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-adr-analysis-server"
      ],
      "env": {
        "PROJECT_PATH": "your-value",
        "OPENROUTER_API_KEY": "your-value",
        "EXECUTION_MODE": "your-value",
        "ADR_DIRECTORY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "adr-analysis": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "mcp-adr-analysis-server"
      ],
      "env": {
        "PROJECT_PATH": "your-value",
        "OPENROUTER_API_KEY": "your-value",
        "EXECUTION_MODE": "your-value",
        "ADR_DIRECTORY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • PROJECT_PATH env
    Path to the project directory to analyze (defaults to current directory)
  • OPENROUTER_API_KEY 机密 env
    OpenRouter API key for AI-powered analysis (required for full execution mode)
  • EXECUTION_MODE env
    Execution mode: 'ce-mcp' (default), 'full' for AI results, or 'prompt-only' for prompts
  • ADR_DIRECTORY env
    ADR directory relative to project path (default: docs/adrs)

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 tosin2013 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 5679 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 5679 个服务器的 79% 更新
  • 基础检查结果等于或优于此分类中其他 5679 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

MCP Adr Analysis Server 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:OPENROUTER_API_KEY

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(2.14.19)于10天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT昨天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT21天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT2个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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

Your ADRs are lying to you. This MCP server catches it — live drift detection validates architectural decisions against your actual code. Plus content safety, decision memory, and 63 tools powered by your host LLM via CE-MCP.

Table of contents

  • What is MCP?
  • Prerequisites
  • Quick Installation
  • Quick Setup
  • Usage Examples
  • Use Cases
  • Technology Stack
  • Project Structure
  • Testing
  • ADR Aggregator Integration
  • Development
  • Troubleshooting
  • Security & Performance
  • Contributing
  • Resources
  • License

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 servers. This server gives your AI assistant the ability to detect ADR drift against live code, mask sensitive content before it leaks, and remember architectural decisions across conversations.

TL;DR

What: MCP server that validates architectural decisions against your actual code — drift detection, content safety, and decision memory Who: AI coding assistants (Claude, Cline, Cursor, Windsurf), enterprise architects, development teams Why: Catch stale ADRs before they cause production incidents — live validation against code evidence, no API key required How: npm install -g mcp-adr-analysis-server → Add to your MCP client → Start analyzing

Key Features: Tree-sitter AST analysis • Security content masking • Drift detection • CE-MCP orchestration directives • 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.
CE-MCPClaude-Enriched MCP — Execution mode where tools return orchestration directives for the host LLM instead of making their own AI calls. Default since v2.14.
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.
Session & Tool-Usage TrackerProject-local tracking of session intents, tool executions, and ADR registrations, with keyword-scored retrieval over JSON snapshots. Supports workflow continuity and tool-usage evidence — not a graph database.
Smart Code LinkingDiscovery of code files related to ADRs and architectural decisions, using keyword extraction and ripgrep search.
ADR AggregatorOptional SaaS integration for syncing and sharing ADR context across teams (ADR_AGGREGATOR_API_KEY).

Author: Tosin Akinosho | Repository: GitHub | Version: 2.14.12

✨ Core Capabilities

🔄 Drift Detection - Validate ADR decisions against live code and infrastructure evidence 🛡️ Content Safety - Detect and mask secrets, PII, and sensitive content automatically 🧠 Decision Memory - Session & tool-usage tracking with keyword-scored retrieval 🏗️ Technology Detection - Identify any tech stack and architectural patterns 📋 ADR Management - Generate, suggest, and maintain Architectural Decision Records 🔗 Smart Code Linking - Discovery of code files related to ADRs and decisions 🚀 Deployment Readiness - Zero-tolerance test validation with hard blocking

📖 [View Full Capabilities →](docs/explanation/index.md) · 📜 [Release policy →](RELEASES.md) · 🗒️ [Changelog →](CHANGELOG.md)

Prerequisites

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:

Network Requirements
  • Internet access required during npm install for native module compilation (tree-sitter incremental code parsers for YAML and 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

# 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 →](docs/tutorials/01-first-steps.md) | [RHEL Setup →](scripts/install-rhel.sh)

⚡ Quick Setup (2 Steps)

  1. Install: npm install -g mcp-adr-analysis-server
  2. Configure Client: Add to Claude Desktop, Cline, Cursor, or Windsurf — no API key required
{

"mcpServers": { "adr-analysis": { "command": "mcp-adr-analysis-server", "env": { "PROJECT_PATH": "/path/to/your/project" } } } }

That's it. The server runs in CE-MCP mode by default — your host LLM (Claude, GPT, etc.) executes the analysis using orchestration directives returned by the tools. No external API key needed.

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)
VS Code (native MCP).vscode/mcp.json in workspace root
CursorCursor Settings → MCP → Add Server

📖 [VS Code Integration Guide →](docs/how-to-guides/vscode-integration.md) — step-by-step setup for Cline, Continue, and VS Code native MCP with example configs.

Optional: OpenRouter Full Mode (legacy)

If you want the server to make its own AI calls (bypassing the host LLM), add an OpenRouter API key:

{

"mcpServers": { "adr-analysis": { "command": "mcp-adr-analysis-server", "env": { "PROJECT_PATH": "/path/to/your/project", "OPENROUTER_API_KEY": "your_key_here", "EXECUTION_MODE": "full" } } } }

Sign up at OpenRouter.ai/keys. This mode is not recommended — CE-MCP produces equivalent results using your existing host LLM context.

Optional: ADR Aggregator integration

{

"mcpServers": { "adr-analysis": { "command": "mcp-adr-analysis-server", "env": { "PROJECT_PATH": "/path/to/your/project", "ADR_AGGREGATOR_API_KEY": "agg_your_key_here" } } } }

Get your API key at adraggregator.com

📖 [Full Configuration Guide →](docs/reference/mcp-client-config.md) | [Client Setup →](docs/reference/environment-config.md)

Execution Modes
CE-MCP (default)Full Mode (legacy)Prompt-Only
Requires API key?NoYes (OPENROUTER_API_KEY)No
ReturnsOrchestration directives for the host LLM to executeServer-side AI analysis resultsPrompts you can paste into any AI chat
Set viaDefault (no env var needed)EXECUTION_MODE=fullEXECUTION_MODE=prompt-only
Best for

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