mcp-bitbucket

Python MCP server for Bitbucket Cloud (REST v2), built with FastMCP. It exposes tools for repositories, pull requests (incl. comments, drafts), branching models, and pipelines so AI clients (e.g., Cursor) can safely automate workflows.

Requirements

• Python 3.10+
• uv (pipx install uv or follow uv docs)
• Bitbucket Cloud account with either:
  • App Password (recommended) for BITBUCKET_USERNAME/BITBUCKET_PASSWORD, or
  • OAuth token via BITBUCKET_TOKEN

Recommended scopes for App Password (adjust to your needs):

• repository:read, pullrequest:read, pullrequest:write
• pipeline:read, pipeline:write (if you will use pipelines tools)

Install (editable)

uv pip install -e .

Docker Usage (HTTP/SSE Transport)

The MCP server runs in a Docker container using HTTP/SSE transport, allowing a single long-running container that handles multiple Cursor connections.

Quick Start

1. Create environment file:

cp .env.example .env
# Edit .env with your Bitbucket credentials

2. Build and start the container:

docker-compose up -d --build

3. Configure Cursor (~/.cursor/mcp.json):

{
  "mcpServers": {
    "bitbucket": {
      "url": "http://localhost:9000/sse"
    }
  }
}

4. Restart Cursor - The Bitbucket MCP server should now be available!

Manual Docker Commands

Build the image:

docker build -t mcp-bitbucket:latest .

Run with docker-compose:

# Start in background
docker-compose up -d

# View logs
docker-compose logs -f

# Stop
docker-compose down

Run with docker directly:

docker run -d \
  --name mcp-bitbucket \
  -p 9000:9000 \
  -e BITBUCKET_USERNAME=your_username \
  -e BITBUCKET_PASSWORD=your_app_password \
  -e BITBUCKET_WORKSPACE=your_workspace \
  -e MCP_TRANSPORT=sse \
  mcp-bitbucket:latest

Health Check

Verify the server is running:

curl http://localhost:9000/sse

Container Management

# Check if running
docker ps | grep mcp-bitbucket

# View logs
docker logs mcp-bitbucket

# Restart
docker restart mcp-bitbucket

# Stop and remove
docker stop mcp-bitbucket
docker rm mcp-bitbucket

Benefits of HTTP/SSE Transport

• Single container: One long-running container handles all requests
• Multiple connections: Cursor can connect/reconnect without spawning new containers
• Better performance: No container startup overhead per request
• Easier debugging: View logs with docker logs
• Health monitoring: Built-in health checks

Multi-Project Setup

If you work on multiple projects with different Bitbucket credentials, you can run multiple containers:

Setup:

1. Create project-specific env files:

cp .env.project1.example .env.project1
cp .env.project2.example .env.project2
# Edit each with the appropriate credentials

2. Start both containers:

docker compose -f docker-compose.project1.yml up -d
docker compose -f docker-compose.project2.yml up -d

3. Configure Cursor with both servers:

{
  "mcpServers": {
    "bitbucket-project1": {
      "url": "http://localhost:9000/sse"
    },
    "bitbucket-project2": {
      "url": "http://localhost:9001/sse"
    }
  }
}

Management:

# Start all projects
docker compose -f docker-compose.project1.yml up -d
docker compose -f docker-compose.project2.yml up -d

# Stop specific project
docker compose -f docker-compose.project1.yml down

# View logs for specific project
docker compose -f docker-compose.project1.yml logs -f

Configuration

Environment variables:

• BITBUCKET_URL: defaults to https://api.bitbucket.org/2.0
• BITBUCKET_TOKEN: OAuth token (optional, alternative to username/password)
• BITBUCKET_USERNAME / BITBUCKET_PASSWORD: Bitbucket username + App Password
• BITBUCKET_WORKSPACE: default workspace slug (optional but convenient)
• FASTMCP_LOG_LEVEL: DEBUG|INFO|... (optional)

Run (stdio server)

BITBUCKET_USERNAME='<user>' \
BITBUCKET_PASSWORD='<app_password>' \
BITBUCKET_WORKSPACE='<workspace>' \
uv run mcp-bitbucket

The server uses stdio and prints little until a client connects.

Debug with MCP Inspector

Expose a FastMCP instance via src/app.py and launch the Inspector:

BITBUCKET_USERNAME='<user>' \
BITBUCKET_PASSWORD='<app_password>' \
BITBUCKET_WORKSPACE='<workspace>' \
uv run --with mcp mcp dev src/app.py --with-editable .

Open the printed URL and call tools like health and listRepositories.

Use with Cursor (Native/Development)

Option 1: Docker (Recommended for Production)

See Docker Usage section above.

Option 2: Direct UV (for Development)

If Cursor runs inside the same Ubuntu WSL2 environment, prefer an absolute path to uv and add editable source to ensure the local tree is used:

{
  "mcpServers": {
    "bitbucket": {
      "command": "/home/nemanja/.local/bin/uv",
      "args": ["run", "--with-editable", "/home/nemanja/projects/mcp/mcp-bitbucket", "mcp-bitbucket"],
      "env": {
        "BITBUCKET_URL": "https://api.bitbucket.org/2.0",
        "BITBUCKET_USERNAME": "your_username",
        "BITBUCKET_PASSWORD": "your_app_password",
        "BITBUCKET_WORKSPACE": "your_workspace",
        "FASTMCP_LOG_LEVEL": "DEBUG"
      }
    }
  }
}

Option 3: WSL Bridge (Windows)

If Cursor runs on Windows (outside WSL), bridge to WSL via:

{
  "mcpServers": {
    "bitbucket": {
      "command": "wsl",
      "args": [
        "bash", "-lc",
        "cd /home/<user>/projects/mcp/mcp-bitbucket && BITBUCKET_USERNAME='your_username' BITBUCKET_PASSWORD='your_app_password' BITBUCKET_WORKSPACE='your_workspace' /home/<user>/.local/bin/uv run mcp-bitbucket"
      ]
    }
  }
}

Tools (high-level)

• health
• listRepositories, getRepository
• getPullRequests, createPullRequest, getPullRequest, updatePullRequest, getPullRequestActivity, approvePullRequest, unapprovePullRequest, declinePullRequest, mergePullRequest, getPullRequestComments, getPullRequestCommits, getPullRequestDiff, addPullRequestComment, addPendingPullRequestComment, publishPendingComments, createDraftPullRequest, publishDraftPullRequest, convertTodraft, getPendingReviewPRs (requires BITBUCKET_USERNAME to identify current reviewer)
• Branching model: get/update at repo and project levels; resolve effective repo model
• Pipelines: list runs, get run, run pipeline, stop run, list/get step(s), step logs

All tools return MCP-compatible responses (text content with pretty-printed JSON, or raw text for diffs/logs).

Troubleshooting

• No tools in client: ensure the command actually starts in your environment (absolute path to uv helps). Add FASTMCP_LOG_LEVEL=DEBUG.
• 401/403: verify App Password scopes and workspace/repo access.
• Workspace missing: set BITBUCKET_WORKSPACE or pass workspace argument to tools.
• Inspector won’t connect: ensure proxy health at http://localhost:6277/health returns { "status": "ok" }. If bridging from Windows to WSL, enable localhost forwarding in WSL.

Security

Treat App Passwords and tokens as secrets. Rotate if exposed.