devin-mcp

devin-mcp

Enables Claude Code to delegate implementation tasks to Devin.

Category
访问服务器

README

Devin MCP Server

An MCP server that enables Claude Code to delegate implementation tasks to Devin.

Installation

Option 1: Install from Local Path (Development)

If you have the devin-mcp repository cloned locally:

# Navigate to the devin-mcp directory
cd /path/to/devin-mcp

# Install with uv (creates venv automatically)
uv pip install -e .

Option 2: Install from Git Repository

# Install directly from git (if repository is public)
uv pip install git+https://github.com/iainmck29/devin-mcp.git

# Or from a specific branch/tag
uv pip install git+https://github.com/iainmck29/devin-mcp.git@main

Option 3: Install as a Published Package

# If published to PyPI (future)
uv pip install devin-mcp

Note: The MCP server needs to be installed in a location where uv can find it. If installing from a local path, use an absolute path or ensure the path is accessible.

Configuration

Set your Devin API key and playbook ID as environment variables:

export DEVIN_API_KEY="your-api-key-here"
export DEVIN_PLAYBOOK_ID="your-playbook-id-here"

Usage

Running the Server

# Via module (using uv run to automatically use project venv)
uv run python -m devin_mcp.server

# Or via CLI entry point
uv run devin-mcp

Claude Code Configuration

Step 1: Get Your Devin API Key

  1. Sign in to Devin
  2. Navigate to your account settings or API section
  3. Generate or copy your API key

Step 2: Locate Claude Code Settings File

The MCP settings file location depends on your OS:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • Linux: ~/.config/Claude/claude_desktop_config.json

Step 3: Configure the MCP Server

Open the settings file and add the devin server configuration. If the file doesn't exist or is empty, create it with this structure:

{
  "mcpServers": {
    "devin": {
      "command": "uv",
      "args": ["run", "python", "-m", "devin_mcp.server"],
      "env": {
        "DEVIN_API_KEY": "your-api-key-here",
        "DEVIN_PLAYBOOK_ID": "your-playbook-id-here"
      }
    }
  }
}

Important Notes:

  • Replace "your-api-key-here" with your actual Devin API key
  • Replace "your-playbook-id-here" with your Devin playbook ID
  • If you installed from a local path, ensure uv is in your PATH
  • The uv command must be able to find the installed devin_mcp package
  • If you installed in a specific virtual environment, you may need to use the full path to uv or activate that environment

Step 4: Restart Claude Code

After saving the configuration file:

  1. Completely quit Claude Code (not just close the window)
  2. Reopen Claude Code
  3. The MCP server should automatically start and connect

Step 5: Verify It's Working

  1. Open Claude Code in any project
  2. Check the MCP status indicator (usually in the bottom status bar)
  3. Try asking Claude: "What MCP tools are available?" or "List the devin tools"
  4. You should see the four Devin tools: devin_run_phase, devin_await_completion, devin_get_status, devin_send_message

Troubleshooting

Server won't start:

  • Verify uv is installed: which uv or uv --version
  • Check that devin_mcp is installed: uv run python -c "import devin_mcp; print('OK')"
  • Check Claude Code logs for error messages

API key errors:

  • Verify the API key is correct in the config file
  • Ensure there are no extra quotes or whitespace around the key
  • Test the API key manually: export DEVIN_API_KEY="your-key" && uv run python -c "from devin_mcp.client import DevinClient; print('OK')"

Tools not appearing:

  • Restart Claude Code completely
  • Check the MCP connection status in Claude Code
  • Verify the config JSON is valid (no trailing commas, proper quotes)

Available Tools

devin_run_phase

Create a new Devin session with a playbook and prompt.

Parameters:

  • prompt (string, required): The task prompt
  • playbook_id (string, optional): The Devin playbook ID. Uses DEVIN_PLAYBOOK_ID env var if not provided.

Returns: { success, session_id, url } or { success: false, error }

devin_await_completion

Poll a session until it reaches a terminal state.

Parameters:

  • session_id (string, required): The session to monitor
  • timeout (integer, optional): Max wait in seconds (default: 600)

Returns: Full session details or raises DevinTimeoutError

devin_get_status

Quick, non-blocking status check.

Parameters:

  • session_id (string, required): The session to check

Returns: { success, session_id, url, status_enum } or { success: false, error }

devin_send_message

Send a follow-up message to a session.

Parameters:

  • session_id (string, required): The session to message
  • message (string, required): The message content

Returns: { success, detail } or { success: false, error }

Example Workflow

# 1. Start a phase (uses DEVIN_PLAYBOOK_ID from environment)
result = devin_run_phase(
    prompt="thoughts/shared/plans/2024-01-15-auth.md, phase 1, branch feature/auth"
)
# Or override with a specific playbook:
# result = devin_run_phase(prompt="...", playbook_id="pb_abc123")
session_id = result["session_id"]

# 2. Wait for completion
session = devin_await_completion(session_id, timeout=600)

# 3. Check result
if session["status_enum"] == "finished":
    print("Phase completed successfully!")
elif session["status_enum"] == "blocked":
    # Send clarification if needed
    devin_send_message(session_id, "Use the existing User model from src/models/user.py")

Development

# Install dev dependencies
uv pip install -e ".[dev]"

# Run tests (using uv run to ensure correct environment)
uv run pytest

# Type check
uv run mypy src/

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