Atlassian Bitbucket MCP Server

This project provides a Model Context Protocol (MCP) server that acts as a bridge between AI assistants (like Anthropic's Claude, Cursor AI, or other MCP-compatible clients) and your Atlassian Bitbucket instance. It allows AI to securely access and interact with your repositories, pull requests, and workspaces in real time.

Overview

What is MCP?

Model Context Protocol (MCP) is an open standard that allows AI systems to securely and contextually connect with external tools and data sources.

This server implements MCP specifically for Bitbucket Cloud, bridging your Bitbucket data with AI assistants.

Why Use This Server?

• Minimal Input, Maximum Output Philosophy: Simple identifiers like workspaceSlug and repoSlug are all you need. Each tool returns comprehensive details without requiring extra flags.
• Rich Code Visualization: Get detailed insights into repositories and code changes with file statistics, diff views, and smart context around code modifications.
• Secure Local Authentication: Credentials are never stored in the server. The server runs locally, so your tokens never leave your machine and you can request only the permissions you need.
• Intuitive Markdown Responses: All responses use well-structured Markdown for readability with consistent formatting and navigational links.
• Full Bitbucket Integration: Access workspaces, repositories, pull requests, comments, code search, and more through a unified interface.

Getting Started

Prerequisites

• Node.js (>=18.x): Download
• Bitbucket Cloud Account

Step 1: Authenticate

Choose one of the following authentication methods:

Option A: Bitbucket App Password (Recommended)

Generate one from Bitbucket App Passwords. Minimum permissions:

• Workspaces: Read
• Repositories: Read
• Pull Requests: Read

Option B: Atlassian API Token

Generate one from Atlassian API Tokens.

Step 2: Configure Credentials

Method A: MCP Config File (Recommended)

Create or edit ~/.mcp/configs.json:

Using Bitbucket App Password:

Using Atlassian API Token:

Method B: Environment Variables

Pass credentials directly when running the server:

Step 3: Connect Your AI Assistant

Configure your MCP-compatible client to launch this server.

Claude / Cursor Configuration:

This configuration launches the server automatically at runtime.

Tools

This section covers the MCP tools available when using this server with an AI assistant. Note that MCP tools use snake_case for tool names and camelCase for parameters.

list_workspaces

List available Bitbucket workspaces.

or:

"Show me all my Bitbucket workspaces."

get_workspace

Get full details for a specific workspace.

"Tell me more about the 'acme-corp' workspace."

list_repositories

List repositories in a workspace.

or:

"List repositories in 'acme-corp'."

get_repository

Get details of a specific repository.

"Show me the 'backend-api' repository in 'acme-corp'."

search

Search Bitbucket content.

Repositories:

Pull Requests:

Commits:

Code:

"Search for 'function getUser' in the 'acme-corp' workspace."

list_pull_requests

List pull requests in a repository.

"Show open PRs in 'frontend-app'."

get_pull_request

Get full details of a pull request, including code diffs and file changes.

"Get PR #42 from 'frontend-app' with all code changes."

list_pr_comments

List comments on a specific pull request.

"Show me all comments on PR #42."

add_pr_comment

Add a comment to a pull request.

General:

Inline:

"Add a comment to PR #42 on line 42."

pull_requests_create

Create a new pull request.

"Create a PR from 'feature/login' to 'main'."

Command-Line Interface (CLI)

The CLI uses kebab-case for commands (e.g., list-workspaces) and options (e.g., --workspace-slug).

Quick Use with npx

Install Globally

Then run directly:

Discover More CLI Options

Use --help to see flags and usage for all available commands:

Or get detailed help for a specific command:

License

ISC License