Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
ADR drift detection, content safety, and decision memory for architectural decisions
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
PROJECT_PATH, OPENROUTER_API_KEY, EXECUTION_MODE, ADR_DIRECTORYValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
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-serverFill in the empty values before running it.
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.
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.
PROJECT_PATH envEXECUTION_MODE envADR_DIRECTORY envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
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
The registry name was verified with the GitHub account tosin2013, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
You need to fill in: OPENROUTER_API_KEY
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).
The GitHub repo last changed –, and the latest version (2.14.19) reached the registry 10 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Context7, Codebase Memory, Exa
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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.
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.
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.
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
| Term | Definition |
|---|---|
| ADR | Architectural Decision Record — A document that captures an important architectural decision along with its context, alternatives considered, and consequences. |
| MCP | Model Context Protocol — An open standard enabling AI assistants to connect to external tools and data sources. |
| CE-MCP | Claude-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-sitter | An 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 Tracker | Project-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 Linking | Discovery of code files related to ADRs and architectural decisions, using keyword extraction and ripgrep search. |
| ADR Aggregator | Optional SaaS integration for syncing and sharing ADR context across teams (ADR_AGGREGATOR_API_KEY). |
Author: Tosin Akinosho | Repository: GitHub | Version: 2.14.12
🔄 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)
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# Option 1: Global installation (recommended for frequent use)
npm install -g mcp-adr-analysis-server
npx mcp-adr-analysis-server
git clone https://github.com/tosin2013/mcp-adr-analysis-server.git cd mcp-adr-analysis-server && npm install && npm run build
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.
📖 [Detailed Installation Guide →](docs/tutorials/01-first-steps.md) | [RHEL Setup →](scripts/install-rhel.sh)
npm install -g mcp-adr-analysis-server{
"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
| 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) |
| VS Code (native MCP) | .vscode/mcp.json in workspace root |
| Cursor | Cursor 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)
| CE-MCP (default) | Full Mode (legacy) | Prompt-Only | |
|---|---|---|---|
| Requires API key? | No | Yes (OPENROUTER_API_KEY) | No |
| Returns | Orchestration directives for the host LLM to execute | Server-side AI analysis results | Prompts you can paste into any AI chat |
| Set via | Default (no env var needed) | EXECUTION_MODE=full | EXECUTION_MODE=prompt-only |
| Best for |
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