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aashari/mcp-server-atlassian-bitbucket

by Various

Node.js/TypeScript MCP server for Atlassian Bitbucket. Enables AI systems (LLMs) to interact with workspaces, repositories, and pull requests via tools (list, get, comment, search)

A

MCP

aashari/mcp-server-atlassian-bitbucket

Added 1 June 2026

#ai #ai-connector #ai-integration #anthropic #atlassian #bitbucket #claude #cli

Overview

An open-source MCP server that allows AI assistants to read and write to Bitbucket workspaces, repositories, and pull requests. It exposes tools for listing, retrieving, commenting, and searching resources. Built with Node.js and TypeScript, it integrates with the Model Context Protocol to give LLMs direct access to version control operations.

Best for

Best for
Teams using Bitbucket who want AI assistants to interact with their repositories and pull requests.

Use cases

  • Automate code review comments on pull requests
  • Search repositories and codebase from an AI chat interface
  • List workspace repositories and get pull request details

Notes

An open-source MCP server that allows AI assistants to read and write to Bitbucket workspaces, repositories, and pull requests. It exposes tools for listing, retrieving, commenting, and searching resources. Built with Node.js and TypeScript, it integrates with the Model Context Protocol to give LLMs direct access to version control operations.

150 stars on GitHub. Last updated 2026-03-06.

Use cases

  • Automate code review comments on pull requests
  • Search repositories and codebase from an AI chat interface
  • List workspace repositories and get pull request details

Pros

  • Lightweight and focused MCP implementation
  • Standard protocol integration makes it compatible with multiple AI clients
  • Active open-source project with 150 stars

Cons

  • Requires running a separate MCP server instance
  • Limited to Bitbucket; no GitHub or GitLab support
  • Depends on Node.js runtime and Bitbucket API credentials

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Lightweight and focused MCP implementation
  • Standard protocol integration makes it compatible with multiple AI clients
  • Active open-source project with 150 stars

Cons

  • Requires running a separate MCP server instance
  • Limited to Bitbucket; no GitHub or GitLab support
  • Depends on Node.js runtime and Bitbucket API credentials