Bitbucket MCP Server
Wire your agent into Bitbucket Cloud to open PRs, comment on reviews, and touch pipelines without browser tab churn.
Overview
bitbucket-mcp is a MCP server for the Build phase that lets agents manage Bitbucket repositories, pull requests, comments, and pipelines through the API.
What is this MCP server?
- Manage Bitbucket repositories, pull requests, and PR comments via MCP
- Interact with Bitbucket Pipelines from agent-driven workflows
- Python PyPI package bitbucket-mcp-py v1.9.0 with stdio transport
- Covers broader Bitbucket API operations beyond read-only git status
- Fits teams still on Bitbucket instead of GitHub for indie SaaS repos
- Package version 1.9.0 on PyPI as bitbucket-mcp-py
- Transport: stdio
- Repository: github.com/lawp09/bitbucket-mcp
Community signal: 2 GitHub stars.
What problem does it solve?
Agent-assisted coding stalls when every Bitbucket PR or pipeline check forces you out of the IDE into the Bitbucket UI.
Who is it for?
Solo builders and tiny teams hosting code on Bitbucket Cloud who want Claude Code or Cursor to drive repo and PR tasks.
Skip if: GitHub-only workflows or builders who want a hosted git skill without Bitbucket credentials.
What do I get? / Deliverables
Your agent can create and update Bitbucket PRs, comment on reviews, and query pipelines via MCP from one session.
- Programmatic repo, PR, comment, and pipeline actions callable by the agent
- Reduced UI context switching during Bitbucket-based build workflows
- API-backed automation for repetitive PR and pipeline checks
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Journey fit
Repository and PR operations are daily Build-phase work while you ship features; pipelines bridge toward Ship but the API surface is primarily dev integration. Integrations is the canonical shelf for third-party VCS and CI APIs that agents call from the editor.
How it compares
Bitbucket API MCP bridge, not a code-review methodology skill or local git CLI wrapper.
Common Questions / FAQ
Who is bitbucket-mcp for?
Developers using Bitbucket Cloud who want MCP tools for repos, pull requests, comments, and pipelines inside AI coding agents.
When should I use bitbucket-mcp?
Use it during feature work when you need the agent to open PRs, respond to review threads, or check pipeline status on Bitbucket.
How do I add bitbucket-mcp to my agent?
Install bitbucket-mcp-py from PyPI, add the stdio MCP server entry in your agent config, and set Bitbucket API credentials with appropriate repo and pipeline scopes.