Skip to main content
Glama

MCP Server Airflow Token

get_dataset

Retrieve datasets from Apache Airflow deployments using their URI, enabling access to stored data for analysis and workflow integration.

Instructions

Get a dataset by URI

Input Schema

NameRequiredDescriptionDefault
uriYes

Input Schema (JSON Schema)

{ "properties": { "uri": { "title": "Uri", "type": "string" } }, "required": [ "uri" ], "type": "object" }

Implementation Reference

  • The handler function that executes the 'get_dataset' tool logic: fetches the dataset by URI from Airflow DatasetApi and returns formatted text content.
    async def get_dataset( uri: str, ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]: response = dataset_api.get_dataset(uri=uri) return [types.TextContent(type="text", text=str(response.to_dict()))]
  • Registers the get_dataset tool in the list of functions returned by get_all_functions(), providing name, description, and read-only flag for MCP server tool addition.
    (get_dataset, "get_dataset", "Get a dataset by URI", True),
  • src/main.py:28-28 (registration)
    Maps APIType.DATASET to get_dataset_functions in the APITYPE_TO_FUNCTIONS dictionary, enabling dynamic retrieval and registration of dataset tools including get_dataset.
    APIType.DATASET: get_dataset_functions,
  • src/main.py:10-10 (registration)
    Imports the get_all_functions from dataset.py, aliased for use in registering dataset tools like get_dataset.
    from src.airflow.dataset import get_all_functions as get_dataset_functions

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/nikhil-ganage/mcp-server-airflow-token'

If you have feedback or need assistance with the MCP directory API, please join our Discord server