An MCP server for Bitbucket Cloud: pull request review, repository and source tools, plus a searchable index of every REST endpoint.
Server has 4 tools with complete schemas and descriptions. Naming follows verb_noun pattern (bb_list_endpoints, bb_request, bb_create_issue, bb_delete_issue). Descriptions are detailed and explain WHEN to use each tool. However, bb_request and bb_list_endpoints descriptions are verbose (300+ chars, exceeding the 200-char baseline for optimal LLM parsing). Parameter descriptions are present and mostly clear, but lack actionable error guidance. Output schemas are not documented, LLMs cannot predict response structure. Error handling is minimal; no recovery guidance provided. Tool composition is sound (single responsibility), but bb_request is a generic escape hatch that could mask missing domain-specific tools.
Create an issue in a Bitbucket repository
Delete an issue from a Bitbucket repository
Search the full Bitbucket Cloud REST API (all endpoints, generated from Atlassian's official OpenAPI spec) to find the right method, path and params for a task. Call this FIRST whenever no purpose-built bb_* tool covers what you need, then pass the result to bb_request. Every whitespace-separated term in `search` must match, so 'pull request comment' narrows better than 'comment'.
Call ANY Bitbucket Cloud 2.0 REST endpoint directly. This is the escape hatch for everything the purpose-built bb_* tools do not wrap - merges, commit comparison, branches and tags, pipelines, code search, webhooks, permissions. Use bb_list_endpoints first to get the exact path and params. Paths are relative to https://api.bitbucket.org/2.0 and must have real values substituted for {placeholders}. Set paginate=true on list endpoints to follow Bitbucket's `next` links and merge all pages.
Output schemas not documented. LLMs cannot predict response structure for any tool, forcing them to guess what fields are returned and risking failed downstream tool chains.
bb_request and bb_list_endpoints descriptions exceed 300 chars (baseline 200 for optimal LLM parsing). Verbose descriptions waste tokens and bury key details.
No error handling guidance. Tools do not explain what to do on failure (retryable vs user-fixable vs fatal). LLMs receive raw errors with no recovery path.
bb_delete_issue is destructive but lacks confirmation or dry-run support. Agents can permanently delete issues without a safety gate.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | C | 62 | 2026-07-28+ | v2 |
bb_request accepts 'raw' parameter but no guidance on when to use it or what format to expect. LLMs may misuse it for structured data.