Airflow (abhishekbhakat) MCP Server
airflow-mcp-server
PyPI
v0.9.1
Published by abhishekbhakat — 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.
MCP Server for Airflow
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 − 4 = 96. 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 |
|---|---|
| −3 | capability blast radius (moderate) — 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 0
Tools 4
Each tool and what it can reach — statically extracted from the published source.
browse_categoriesingests untrusted inputback_to_categoriesno sensitive capabilityget_current_categoryno sensitive capabilityselect_categoryno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (4 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 |
|---|---|---|---|---|
v0.9.1 latest |
A 96/100 | 0 | 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 airflow-mcp-server --online --registry pypiOther implementations of Airflow 3
Independent packages implementing the same tool, scanned with the same engine. Compare all 4 side by side →
Airflow MCP server — DAG list, runs, task instances, log tails, trigger and clear over the Airflow REST API
MCP server for Apache Airflow REST API
本项目是一个与 Apache Airflow 集成的 Model Context Protocol (MCP) 服务器，提供多种工具来管理和监控 Airflow 的 DAG 运行。它支持触发 DAG、获取 DAG 状态、回填数据、获取日志等操作。
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