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bitbucket-mcp

bitbucket-mcp

by lawp09
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.5/5.0

    Scored across 74 tools

    Disambiguation4/5

    Despite 74 tools, most have a distinct resource+action target (PRs, issues, commits, files, pipelines, deployments, permissions). A few overlap: create_draft_pull_request is a subset of create_pull_request's draft flag, get_pull_request_comment(s) singular/plural are easy to mix up, and submit_pull_request_batch_review partially duplicates add_pull_request_comment + approve_pull_request, though its aggregation purpose is documented.

    Naming Consistency3/5

    The dominant pattern is verb_noun (create_pull_request, resolve_pull_request_comment), which is followed widely. However, list operations are inconsistently named: list_repositories/list_commits/list_issues vs get_repository_tags/get_pull_request_comments/get_commit_comments/get_effective_default_reviewers, which all return collections. The get_/list_ distinction becomes unreliable for selection.

    Tool Count2/5

    74 tools is far beyond the 25+ threshold and is a very heavy surface for an agent to navigate, even given Bitbucket's broad domain. Several niche areas (deployment variables, pipeline caches, schedule executions, branch restrictions) each consume tool slots, increasing selection cost.

    Completeness3/5

    Read coverage is excellent across PRs, issues, commits, files, pipelines, deployments, and permissions, but the write surface has notable gaps: there is no merge_pull_request (only decline), no repository/branch create-update-delete, and pipeline variables/schedules/environments are read-only. These omissions block common lifecycle workflows.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive

    Resources