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MCP Adr Analysis Server

by tosin2013version 2.14.19i★ –iRuns on your computer
Registry nameio.github.tosin2013/mcp-adr-analysis-server

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory
  • You need to fill in: OPENROUTER_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: PROJECT_PATH, OPENROUTER_API_KEY, EXECUTION_MODE, ADR_DIRECTORY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into 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"
      }
    }
  }
}

Run this in your terminal

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

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.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"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "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"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • PROJECT_PATH env
    Path to the project directory to analyze (defaults to current directory)
  • OPENROUTER_API_KEY secret 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)

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account tosin2013, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 5676 servers in this category
  • Published to the registry more recently than 79% of the other 5676 servers in this category
  • Basic checks equal to or better than 100% of the other 5676 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is MCP Adr Analysis Server safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: OPENROUTER_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (2.14.19) reached the registry 10 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday
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Codebase Memory

by DeusData

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

Runs on your computer★ 48,148MITUpdated 21 days ago
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Exa

by exa-labs

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

Runs in the cloud★ 5,213MITUpdated 2 months ago
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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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