Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Analyzes codebases with tree-sitter and generates AGENTS.md files for AI coding agents.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"agents-md-generator": {
"command": "uvx",
"args": [
"agents-md-generator"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add agents-md-generator -- uvx agents-md-generator프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"agents-md-generator": {
"command": "uvx",
"args": [
"agents-md-generator"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"agents-md-generator": {
"type": "stdio",
"command": "uvx",
"args": [
"agents-md-generator"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 nushey 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.6.1)은 2개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, TF Rooms
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
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제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
MCP server that analyzes codebases with [tree-sitter](https://tree-sitter.github.io/) and generates [`AGENTS.md`](https://agents.md/) files.
Python · C# · TypeScript · JavaScript · Go
Installation · Usage · Configuration · How It Works · Contributing
Compatible with any MCP-capable client: Claude Code, Gemini CLI, Cursor, Windsurf, Codex CLI, and others.
The server exposes three tools with a clear separation of concerns:
No large data travels over the MCP wire.
Requirements: Python 3.11+, Git, and any MCP-compatible client.
See [INSTALLATION.md](https://github.com/nushey/agents-md-generator/blob/main/INSTALLATION.md) for the full guide including prerequisites and troubleshooting.
pip install agents-md-generator
agents-md-generator setup
The setup wizard detects your installed clients, asks whether to configure globally or per-project, and patches the config files automatically. Supports Claude Code, Gemini CLI, Cursor, Windsurf, and Codex CLI.
If you have uv installed, uvx runs the package without a prior install step. Add the entry manually to your client's MCP config:
{
"mcpServers": { "agents-md": { "command": "uvx", "args": ["agents-md-generator"] } } }
For Claude Code specifically:
claude mcp add agents-md -- uvx agents-md-generator
claude mcp adddefaults to--scope local(current project only). Add-s userto register it for all projects.
Once registered, ask your AI client:
"Generate the AGENTS.md for this project"
The client will call generate_agents_md automatically. To scan a different directory:
"Generate the AGENTS.md for the project at /path/to/project"
| Tool | Purpose |
|---|---|
generate_agents_md | Main entry point. Runs the pipeline internally, embeds writing rules into the payload, and returns chunked read instructions. Use this to create or update AGENTS.md. |
scan_codebase | Standalone context tool. Analyzes the codebase and returns a pure data payload with no AGENTS.md mandate. Use this when you need architectural context for any other task. |
read_payload_chunk | Streams the payload written by either tool in chunks until has_more is false. |
generate_agents_md
| Parameter | Type | Default | Description |
|---|---|---|---|
project_path | string | "." | Path to the project root |
scan_codebase
| Parameter | Type | Default | Description |
|---|---|---|---|
project_path | string | "." | Path to the project root |
force_full_scan | boolean | false | Ignore cache and rescan everything when explicitly set to true. |
read_payload_chunk
| Parameter | Type | Default | Description |
|---|---|---|---|
project_path | string | "." | Must match the path used in the preceding tool call |
chunk_index | integer | — | Zero-based chunk index. Increment until has_more is false |
The generated AGENTS.md follows the agents.md open standard. It is written as a README for AI agents, not as documentation for humans. Sections include:
| Section | Contents |
|---|---|
| Project Overview | Tech stack and top-level architecture shape |
| Architecture & Data Flow | Detected layers or domains with data flow direction |
| Conventions & Patterns | Naming rules, export contracts, import rules, how to add new entities end-to-end |
| Environment Variables | Variables detected in source files and .env.example |
| Setup Commands | Exact install and run commands from package.json, Makefile, etc. |
| Development Workflow | Build, watch, and dev server commands |
| Testing Instructions | Test commands and framework info (if detected) |
| Code Style | Lint/format commands (if config files detected) |
| Build and Deployment | CI pipeline info (if detected) |
Sections with no detected data are omitted entirely.
AGENTS.md content anywayAGENTS.mdFor large codebases the analysis payload can be too big to return inline over the MCP wire. The server handles this transparently through read_payload_chunk.
Scans run in a separate process with stage progress notifications and a five-minute timeout. Cancellation stops the scan worker. Only one scan per project can run at a time in a server instance; use .agents-config.json to narrow repositories that exceed the time limit.
Generation always assembles a current snapshot, reusing cached symbols for unchanged source files. An interrupted generation can be retried even after its payload was consumed or another scan ran. The client remains responsible for writing AGENTS.md.
Serialized payloads are capped at 300,000 characters. Dropped analysis sections are recorded in metadata.degradations and metadata.truncated_sections. Existing AGENTS.md content and writing instructions are preserved; if these alone exceed the budget, the tool returns an error instead of truncating the document.
generate_agents_md flow
generate_agents_md runs the pipeline internally, writes the payload to disk (including AGENTS.md writing rules), and returns total_chunks with read instructionsread_payload_chunk(project_path, chunk_index=0), then increments chunk_index until has_more is falsedata fields — the payload contains the rules and analysis data needed to write AGENTS.mdscan_codebase flow (pure context, no AGENTS.md mandate)
scan_codebase runs the analysis and writes a pure data payload to diskread_payload_chunkThis flow is pure MCP — no filesystem access required from the client side. Any MCP-compatible client can follow it.
All runtime artifacts are stored outside your project, in the user cache directory:
~/.cache/agents-md-generator/<project-hash>/cache.json ← incremental scan cache
The is a SHA-256 of the project's absolute path — unique per project. Nothing is written to your repository.
Note: The server also writes a temporary
payload.jsonto this directory during analysis, but it is managed entirely by theread_payload_chunktool and deleted automatically after the last chunk is read. You never need to access it directly.
Create .agents-config.json at your project root to customize behavior. This file is optional — all fields have defaults, and you can commit it to share settings with your team.
Full default configuration
{
"project_size": "medium", "exclude": [ "/node_modules/", "/bin/", "/obj/", "/.git/", "/dist/", "/build/", "/__pycache__/", "**/*.min.js", "**/*.min.css", "**/*.bundle.js", "/vendor/", "/packages/", "/.venv/", "/venv/", "/bower_components/", "/app/lib/", "/wwwroot/lib/", "/wwwroot/libs/", "/static/vendor/", "/public/vendor/", "/assets/vendor/", "/site-packages/" ], "include": [], "languages": "auto", "agents_md_path": "./AGENTS.md", "max_file_size_bytes": 1048576 }
| Key | Default | Description |
|---|---|---|
project_size | "medium" | Project scale — tunes all internal caps and thresholds (see Project Size Profiles) |
exclude | (see above) | Glob patterns to exclude from analysis |
include | [] | If non-empty, only analyze files matching these patterns |
languages | "auto" | "auto" detects all supported languages, or pass a list like ["typescript", "python"] |
agents_md_path | "./AGENTS.md" | Output path for the generated file |
max_file_size_bytes | 1048576 | Files larger than this are skipped (default: 1 MB) |
| Variable | Default | Description |
|---|---|---|
AGENTS_MD_LOG_LEVEL | INFO | Server log verbosity. Set to DEBUG to see per-file analysis details. Valid values: DEBUG, INFO, WARNING, ERROR |
The project_size setting controls how aggressively the payload is compressed. A single knob tunes all internal caps — methods per class, symbols per file, directory aggregation, route caps, tree depth, and impact filtering.
| Profile | Lines (guidance) | Impact filter | Description |
|---|
| "small" | 0–15k | medium | Generous caps — nearly
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