Bitbucket Python MCP Server
bitbucket-python-mcp
PyPI
v0.2.2
Published by clikader — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
A Model Context Protocol (MCP) server for BitBucket Cloud operations
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 7 = 93. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
| Points | Adoption-risk factor |
|---|---|
| −6 | capability blast radius (high) — client exposure if the model is manipulated |
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
Findings 1
high Shell/command execution in server code (src/bitbucket_mcp/config.py)MTC-SRC-002
In the server's implementation (`src/bitbucket_mcp/config.py:93`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: y: result = subprocess.run( ["git", "remote", "get-url", remote_name], captu
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/bitbucket_mcp/config.py
Tools 32
Each tool and what it can reach — statically extracted from the published source.
create_pull_requestnetwork egressadd_memoryno sensitive capabilityadd_pull_request_commentno sensitive capabilityapprove_pull_requestno sensitive capabilitycreate_branchno sensitive capabilitycreate_repositoryno sensitive capabilitydelete_branchno sensitive capabilitydelete_memoryno sensitive capabilitydelete_repositoryno sensitive capabilityget_branchno sensitive capability
Show 22 more tools ↓
get_current_git_branchno sensitive capabilityget_current_userno sensitive capabilityget_default_reviewersno sensitive capabilityget_file_contentno sensitive capabilityget_pull_requestno sensitive capabilityget_pull_request_commentsno sensitive capabilityget_pull_request_diffno sensitive capabilityget_relevant_memoriesno sensitive capabilityget_repositoryno sensitive capabilityget_repository_contentsno sensitive capabilitylist_branchesno sensitive capabilitylist_memoriesno sensitive capabilitylist_pull_requestsno sensitive capabilitylist_repositoriesno sensitive capabilitylist_workspace_membersno sensitive capabilityremember_from_pr_commentno sensitive capabilityrequest_changesno sensitive capabilitysearch_codeno sensitive capabilitysearch_memoriesno sensitive capabilitysearch_repositoriesno sensitive capabilitysearch_workspace_usersno sensitive capabilityupdate_repositoryno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (32 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Versions 1
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v0.2.2 latest |
A 93/100 | 1 | 1.13.0 | 2026-08-25 |
Embed this score
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
Verify this score yourself
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
npx mcptrustchecker scan bitbucket-python-mcp --online --registry pypiMore in Developer Tools
Hotel booking MCP server — 300K+ properties, real confirmation numbers, loyalty programs. Builders monetize every booking via Stripe Connect. The first MCP server that completes real hotel reservations inside AI conversations.
Manage AdGuard Home through AI assistants
Read-only Azure DevOps for MCP clients using only your existing browser session — no PAT, no Azure CLI. Browse work items, pull requests, comments, attachments and Artifacts feeds across every project, repo and feed you can access.
MCP server for Adobe Experience Manager Assets integration development
Servidor MCP para el tiempo oficial de España (API pública OpenData de AEMET). Predicción, observación y avisos como herramientas MCP tipadas.
A standalone MCP stdio bridge for Affinity by Canva's local MCP SSE server.