Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/mo-umer977/mcp-server-for-airflow/agents-mdgit clone --depth 1 https://github.com/MO-Umer977/MCP-Server-for-AirflowWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/mo-umer977/mcp-server-for-airflow/agents-md)<a href="https://agentmods.dev/instructions/mo-umer977/mcp-server-for-airflow/agents-md"><img src="https://agentmods.dev/badge/instructions/mo-umer977/mcp-server-for-airflow/agents-md.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01369 | $0.01369 |
| Opus 5 | $0.00685 | $0.00685 |
| Sonnet 5 | $0.00274 | $0.00274 |
| Haiku 4.5 | $0.00137 | $0.00137 |
Grade A, and why
MCP-Server-for-Airflow AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to airflow-mcp-server AGENTS.md — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Airflow MCP — Agent Ramp-up Guide
Mission
The repo ships two complementary MCP deliverables that sit in front of the Airflow 3 REST API:
- airflow-mcp-server – an advanced FastMCP deployment with hierarchical discovery, safe/unsafe modes, transport flexibility, and future prompt/resource hooks.
- airflow-mcp-plugin – a lightweight Airflow webserver plugin that simply exposes the Airflow instance’s REST API as MCP tools at
/mcp.
Both surfaces expose Airflow operations as MCP tools, but choose based on runtime model:
- Server runs as a separate process alongside Airflow and is suited for richer agent workflows or multi-tenant orchestration.
- Plugin runs in-process with Airflow and is the easiest path to add MCP access to an existing Airflow deployment without managing another service.
High-level Architecture
airflow-mcp-server (CLI app)
- CLI entrypoint:
src/airflow_mcp_server/__init__.pyexposes Click flags to select safe/unsafe mode, static vs hierarchical tooling, and transport (stdio,streamable-http,sse). It validates configuration viaAirflowConfigand dispatches to the asyncserve_safeorserve_unsaferunners. - Configuration:
AirflowConfig(config.py) requires bothbase_urlandauth_token(JWT). CLI flags may be overridden byAIRFLOW_BASE_URLandAUTH_TOKENenvironment variables. - Server runners:
server_safe.py(GET-only) andserver_unsafe.py(all methods) fetch the Airflow OpenAPI spec once at startup, build anhttpx.AsyncClientwith the caller’s JWT, attach resources/prompts placeholders, and run FastMCP on the selected transport. - Tool generation:
- Static mode: FastMCP autogenerates one tool per OpenAPI operation via
FastMCP.from_openapi. - Hierarchical mode:
HierarchicalToolManagergroups operations by OpenAPI tag (“category”), keeps navigation tools (browse_categories,select_category,get_current_category), and mounts category-specific FastMCP sub-servers. Utilities live inutils/category_mapper.py.
- Static mode: FastMCP autogenerates one tool per OpenAPI operation via
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 77 lines · 1,369 tokens per session scan A f63318fe9270
MCP-Server-for-Airflow AGENTS.md is an instructions file published in the GitHub repository MO-Umer977/MCP-Server-for-Airflow (0 stars, last pushed 1mo ago), licensed MIT. It adds 1,369 tokens to every session, about $0.0068 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to airflow-mcp-server AGENTS.md, differing in 0 lines, and is treated as a copy.
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