adr-skills

adr-skills

Automatically generates Architecture Decision Records (ADRs) from Claude Code conversations using Claude Opus. Features AI quality review, duplicate detection, and dependency graph.

Category
访问服务器

README

adr-skills

adr-skills is an MCP server for Claude Code that automatically captures development conversations and uses Claude Opus to generate, review, and manage Architecture Decision Records (ADRs).

TL;DR: Install once, and every Claude Code session ends with a structured ADR saved to ~/.adr-mcp/adrs/ — no manual writing required.

adr-skills MCP server

What problem does this solve?

Engineering teams make dozens of architectural decisions every week — which database to use, how to handle auth, whether to go monolith or microservices — but rarely write them down. Months later, nobody remembers why Redis was chosen over Memcached, or why the team avoided GraphQL.

adr-skills solves this by turning your existing Claude Code conversations into permanent, searchable ADR documents automatically.

How it works

  1. You have a normal development conversation in Claude Code
  2. When the session ends, the Stop Hook captures the transcript
  3. Claude Opus analyzes the conversation and extracts the architectural decision
  4. A structured markdown ADR is saved to ~/.adr-mcp/adrs/ADR-0001-*.md
  5. Use review_adr to score quality, link_adrs to map dependencies, check_stale_adrs to surface outdated decisions

Features

  • Auto session capture — Stop Hook saves conversations automatically on Claude Code exit; no manual steps
  • AI-powered ADR generation — Claude Opus extracts context, decision, and consequences from raw conversation
  • AI quality review — Scores ADR completeness 0–100 and flags missing context, unconsidered alternatives, or optimistic consequences
  • Duplicate detection — Warns when a new decision overlaps with a past one before saving
  • Markdown export — Every ADR exported as ADR-NNNN-slug.md, ready to commit alongside your code
  • Status lifecycle — Track decisions through Proposed → Accepted → Deprecated → Superseded
  • Dependency graph — Link ADRs with related_to, conflicts_with, depends_on and visualize relationships
  • Stale ADR alerts — Surface Accepted decisions older than N months that may need revisiting
  • Keyword search — Find past decisions by technology name (e.g. Redis, JWT, PostgreSQL)
  • Timeline view — Full decision history per project, correlated with git commits

How is this different from existing ADR tools?

Tool Auto-capture from chat AI generation Quality review MCP server
adr-skills ✅ Claude Opus
adr-tools (CLI)
mcp-adr-analysis-server ✅ OpenRouter
claude-historian-mcp
log4brains

No existing tool combines automatic conversation capture with AI-powered ADR generation in a single MCP server. There is an open feature request on the Anthropic repo for native ADR support — adr-skills fills that gap today.

Installation

git clone https://github.com/wooxogh/adr-mcp-setup.git
cd adr-mcp-setup
npm install

Register with Claude Code

claude mcp add adr-skills node /absolute/path/to/adr-mcp-setup/index.js

Environment setup

cp .env.example .env
# Add your ANTHROPIC_API_KEY to .env

Without the API key, generate_adr falls back to keyword-based extraction and review_adr is unavailable. .env is in .gitignore — your key will never be committed.

Enable auto session capture (Stop Hook)

Add to ~/.claude/settings.json:

{
  "hooks": {
    "Stop": [{
      "matcher": "",
      "hooks": [{
        "type": "command",
        "command": "node /absolute/path/to/adr-mcp-setup/hook.js"
      }]
    }]
  }
}

Tools (9 total)

Tool Description Requires API key
save_session Save a conversation to the database
generate_adr Auto-generate an ADR from a session ❌ (AI mode: ✅)
review_adr Score ADR quality and get improvement suggestions
update_adr_status Transition ADR through its lifecycle
link_adrs Create relationships between ADRs
get_adr_graph Visualize the ADR dependency graph
check_stale_adrs Find old Accepted ADRs that need revisiting
search_decisions Keyword search across all past decisions
get_timeline Decision history for a project

generate_adr example output

# ADR-1: Adopt Redis as the caching layer

## Status
Accepted

## Context
We needed pub/sub support for real-time notifications.
Memcached only handles simple key-value caching and could not meet this requirement.

## Decision
We adopted Redis as both cache and message broker.
It supports pub/sub, TTL, and persistence, and the team already has operational experience with it.

## Consequences
Real-time features can now be implemented without a separate message broker.
We must account for Redis operational costs and treat it as a potential single point of failure.

review_adr example output

## ADR-1 Review — Score: 62/100

Good context, but decision rationale and risk coverage need work.

### Issues
🔴 [decision] No alternatives were considered before choosing Redis
🟡 [consequences] Risks are mentioned but mitigation strategies are missing

### Suggestions
1. Explicitly document why Memcached was rejected
2. Add a rollback plan if Redis becomes a bottleneck

get_adr_graph example output

## ADR Dependency Graph

### depends on
  ADR-5 "Use JWT for auth"  →  ADR-2 "Adopt Redis as cache"

### conflicts with
  ADR-7 "Move to stateless sessions"  ✕  ADR-2 "Adopt Redis as cache"

FAQ

Q: Do I need an Anthropic API key? No. Without a key, generate_adr uses keyword extraction as a fallback. With a key, Claude Opus produces significantly more accurate ADRs and review_adr becomes available.

Q: Where are ADRs stored? Two places: SQLite database at ~/.adr-mcp/sessions.db and markdown files at ~/.adr-mcp/adrs/. The markdown files are git-committable.

Q: Can I use this without the Stop Hook? Yes. Call save_session manually with your conversation text, then generate_adr with the returned session ID.

Q: Does this work with other AI assistants besides Claude? The MCP server protocol is open, but the Stop Hook is Claude Code-specific. The database and markdown exports are tool-agnostic.

Q: How does duplicate detection work? When generating an ADR, adr-skills extracts significant keywords from the title and decision text and queries for overlapping past ADRs. Matches are shown as warnings — the new ADR is still saved.

Q: What ADR format does this use? The Michael Nygard ADR format (Title, Status, Context, Decision, Consequences), which is the most widely adopted format in the software industry.

Project structure

adr-mcp-setup/
├── index.js      ← MCP server — 9 tool definitions and routing
├── db.js         ← SQLite CRUD (sessions, adrs, adr_relations tables)
├── adr.js        ← ADR extraction and AI review logic (Claude Opus)
├── hook.js       ← Claude Code Stop Hook for automatic session capture
├── .env.example  ← Environment variable template
└── package.json

Database: ~/.adr-mcp/sessions.db ADR files: ~/.adr-mcp/adrs/ADR-NNNN-slug.md

Requirements

  • Node.js 18+
  • Claude Code CLI
  • Anthropic API Key (optional — required for AI generation and review)

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选