apache-airflow-mcp-server AGENTS.md

apache-airflow-mcp-server AGENTS.md is an instructions file for Codex, OpenCode from madamak/apache-airflow-mcp-server. It costs 1,534 tokens per session, scanned A, original, Apache-2.0.

Project instructions for an Airflow Model Context Protocol server that connects agents to Apache Airflow, a system for scheduling and running workflows.

In plain words
What is it for?
Use them when adding or changing tools for Airflow workflows, runs, tasks, logs, datasets, or instance connections.
Why use it?
They define where business logic belongs, how Airflow instances and authentication are configured, and how read-only and write operations are handled.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/madamak/apache-airflow-mcp-server/agents-md
Clone the repo
git clone --depth 1 https://github.com/madamak/apache-airflow-mcp-server

Made for: Codex, OpenCode.

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README.md
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Per session 1,534 This file is loaded in full into every session.
When invoked 1,534 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.01534 $0.01534
Opus 5 $0.00767 $0.00767
Sonnet 5 $0.00307 $0.00307
Haiku 4.5 $0.00153 $0.00153

Measured 5d ago against content hash 0903b04a5ffa, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

apache-airflow-mcp-server 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.

AGENTS.md · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Guidance for AI Agents working on the Airflow MCP Server. This file orients you at the package level (what belongs where, how to extend safely). For module-level guidance, see src/airflow_mcp/AGENTS.md. For tests, see tests/AGENTS.md.

Project Layout

  • src/airflow_mcp/
    • server.py: FastMCP entrypoint. Registers tools and HTTP routes. Thin wrappers only. Write tools are registered through the write_tool decorator, which is a no-op in read-only mode.
    • tools/: Business logic for MCP tools (structured dict outputs; FastMCP serializes). No FastMCP or web concerns. One module per domain (dags.py, runs.py, tasks.py, task_logs.py, datasets.py, instances.py); shared helpers in _common.py.
    • registry.py: Instance registry loader (YAML with ${VAR} env substitution, or a single instance built from AIRFLOW_MCP_HOST/credentials env vars) and cached accessor.
    • client_factory.py: Builds cached apache-airflow-client clients per instance; applies auth, SSL, timeouts. Handles both client majors: instances with api_version: v1 use the 2.x codegen (airflow_client.client.apis), api_version: v2 uses the 3.x codegen (top-level API classes, JWT auth via /auth/token). get_api_family(instance) is the branch point tools use for version-specific calls.
    • url_utils.py: URL resolver/builder (instance detection, dag/task/run extraction, UI URL construction).
    • validation.py: Input validation (safe identifier patterns; SSRF guard via host check in resolver).
    • observability.py: Structured logging with request_id; common operation logger.
  • errors.py: Error types and handle_errors decorator (raises MCP ToolError with compact JSON payload).
    • config.py: Pydantic settings (AIRFLOW_MCP_*).
  • tests/: Unit and integration tests (mocked client; no real network).
  • examples/instances.yaml: Example instance registry used by tests.

Development Workflow

  • Install & sync deps with uv sync.
  • Run locally:
    • uv run airflow-mcp --transport stdio
    • uv run airflow-mcp --transport http --host 127.0.0.1 --port 8765
  • Test & lint before pushing:
    • uv run pytest
    • uv run ruff check .
  • Optional format pass: uv run ruff format .
  • Commit hygiene: run tests + lint locally prior to opening a PR.

Read the full file on GitHub · 85 lines

Changes

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.

  1. 5d ago First seen · 85 lines · 1,534 tokens per session scan A 0903b04a5ffa

Subscribe to this mod's changes

apache-airflow-mcp-server AGENTS.md is an instructions file published in the GitHub repository madamak/apache-airflow-mcp-server (2 stars, last pushed 11d ago), licensed Apache-2.0. It adds 1,534 tokens to every session, about $0.0077 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.