Skip to main content

Model Context Protocol (MCP) server for Airflow database integration

Project description

MCP Airflow Database

A Model Context Protocol (MCP) server for interacting with Airflow databases.

Setup with Poetry

Prerequisites

  • Python 3.8 or higher
  • Poetry installed on your system

Installation

  1. Clone this repository:

    git clone <your-repository-url>
    cd mcp-airflow-db
    
  2. Install dependencies with Poetry:

    poetry install
    
  3. Configure your environment: Create a .env file with your database connection string:

    DATABASE_URL=postgresql://airflow:airflow123@localhost:5432/airflow
    

Running the MCP Server

Run the server with Poetry:

poetry run python src/server.py

Or activate the Poetry environment first:

poetry shell
python src/server.py

Using with Smithery

This MCP can be used with Smithery directly as configured in the smithery.yaml file. Make sure to provide the DATABASE_URL configuration when starting the server.

Available Tools

  • failed_runs: Query failed Airflow DAG runs within a specified time period.
  • query: Execute SQL queries directly against the Airflow database.

License

[Your License]

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mcp_airflow_postgres-0.1.1.tar.gz (33.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mcp_airflow_postgres-0.1.1-py3-none-any.whl (4.1 kB view details)

Uploaded Python 3

File details

Details for the file mcp_airflow_postgres-0.1.1.tar.gz.

File metadata

  • Download URL: mcp_airflow_postgres-0.1.1.tar.gz
  • Upload date:
  • Size: 33.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for mcp_airflow_postgres-0.1.1.tar.gz
Algorithm Hash digest
SHA256 d53e952fa93afb1d465a859c5e456d8a48199689631dd460690d320113f2c560
MD5 4df08e77ca43199a098dbf05993d2593
BLAKE2b-256 2959552149fe88d75cd3ba12419830260352e73f7c448f3881c2dd95b6ce8842

See more details on using hashes here.

File details

Details for the file mcp_airflow_postgres-0.1.1-py3-none-any.whl.

File metadata

File hashes

Hashes for mcp_airflow_postgres-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 5c42b56a4c463e66f305447d9afbf46447d135e99530a9081e808d05e03c9baa
MD5 1ccdf7c7ee78ff7dccda7ffda1014241
BLAKE2b-256 aa6be82ebc0a8532ba2954dcce0f6614005d0a997db7523dd9cd62162599b0fe

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page