devin-mcp

devin-mcp

Enables Claude Code to delegate implementation tasks to Devin.

Category
Visit Server

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/

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured