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nixtla-airflow-operator

v1.0.0

Real Apache Airflow tooling for TimeGPT forecasting pipelines. Generate production-ready DAGs (BigQuery / Snowflake / Postgres / S3 sources), AST + DagBag-based DAG validation with credential lint, real Airflow Connection JSON for 5 source types, and pytest test modules that load the DAG via DagBag.

Claude Code1 MCP serverstdio

By Jeremy LongshoreLicense: MIT11 GitHub starsUpdated 3 weeks ago

Directory evidence

Runtimes
Claude Code
Parsed components
1 skill or MCP entry
Source updated
Sep 25, 2026
Manifest status
Canonical path parsed

The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →

Install nixtla-airflow-operator for Claude Code

Installs for the current user
claude plugin marketplace add IchenDEV/agent-plugin-mkt
claude plugin marketplace update agent-plugin-marketplace
claude plugin install nixtla-airflow-operator@agent-plugin-marketplace

Paste and run these commands in a terminal with Claude Code. They add and refresh the PluginsMP catalog, then install this plugin.

The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.

Get the source manually
git clone https://github.com/jeremylongshore/plugins-nixtla

Clone the source repository, then follow its setup instructions to add the plugin to a compatible client. The plugin root is 005-plugins/nixtla-airflow-operator/.

Plugin files

005-plugins/nixtla-airflow-operator/
├── .claude-plugin/plugin.json
└── .mcp.json

MCP servers1

nixtla-airflow-operatorstdio
command
python
args
scripts/airflow_mcp.py

Plugin manifests1

005-plugins/nixtla-airflow-operator/.claude-plugin/plugin.json
{
  "name": "nixtla-airflow-operator",
  "version": "1.0.0",
  "description": "Real Apache Airflow tooling for TimeGPT forecasting pipelines. Generate production-ready DAGs (BigQuery / Snowflake / Postgres / S3 sources), AST + DagBag-based DAG validation with credential lint, real Airflow Connection JSON for 5 source types, and pytest test modules that load the DAG via DagBag.",
  "author": {
    "name": "Jeremy Longshore",
    "email": "[email protected]",
    "url": "https://github.com/jeremylongshore"
  },
  "homepage": "https://github.com/jeremylongshore/plugins-nixtla",
  "repository": "https://github.com/jeremylongshore/plugins-nixtla",
  "license": "MIT",
  "keywords": [
    "nixtla",
    "timegpt",
    "airflow",
    "dag",
    "orchestration",
    "forecasting"
  ],
  "commands": "./commands"
}

For maintainers

If you maintain this plugin, link to this source-backed listing from your README so users can review its manifest and indexed components.

[nixtla-airflow-operator on Agent Plugins Marketplace](https://pluginsmp.com/plugins/nixtla-airflow-operator)