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OpenML MCP Server

OpenML MCP Server

Local
github.com/mallochioScience & Education0Updated 79w ago

About OpenML MCP Server

OpenML MCP Server connects MCP clients to the public OpenML API. It exposes tools for exploring datasets, tasks, experiment flows, runs, evaluations, setups, and studies, with filtering where supported.

Key features

  1. 01Query datasets and their descriptions
  2. 02Explore tasks, flows, and runs
  3. 03Retrieve evaluations, setups, and studies
  4. 04Filter entity listings where supported

Use cases

  1. 01Inspect an OpenML dataset from an MCP client
  2. 02Find classification tasks with API filters
  3. 03Retrieve details for an experiment run

MCP support

An MCP server that exposes major OpenML GET endpoints as tools for MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

⛑️ Work in Progress!

OpenML MCP Server

PyPI Python Versions License: MIT

An MCP (Model Context Protocol) server that allows clients (like Claude Desktop) to interact with the public OpenML API.

This server exposes various OpenML API endpoints as MCP tools, enabling queries for datasets, tasks, flows, runs, and more directly from within an MCP-compatible client.

Table of Contents

Features

  • Provides MCP tools corresponding to major OpenML GET endpoints.
  • Query datasets, tasks, flows, runs, evaluations, setups, studies.
  • List entities with filtering capabilities (where supported by the API).
  • Built using the mcp Python SDK (FastMCP).

Installation and Usage

For End Users

These instructions explain how to use this server with an MCP client like Claude Desktop.

Prerequisites:

  1. Claude Desktop: Ensure you have the latest version installed (Download here).
  2. uv (Python Package Installer): This server is run using uv. Install it once if you don't have it:
    • macOS / Linux:
      curl -LsSf https://astral.sh/uv/install.sh | sh
      
      (Restart your terminal after installation)
    • Windows (PowerShell):
      powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
      
      (Restart your PowerShell terminal after installation)
For Developers
  1. Clone the Repository:
    git clone https://github.com/your-repo/openml-mcp-server.git
    cd openml-mcp-server
    
  2. Install Dependencies:
    uv sync
    

Configuration

  1. Edit Claude Desktop Config:

    • Open Claude Desktop -> Menu -> Settings... -> Developer -> Edit Config.
    • This opens claude_desktop_config.json.
  2. Add Server Configuration:

    • Add the following block inside the mcpServers object (create mcpServers if it doesn't exist):

      {
        "mcpServers": {
          "openml-explorer": {
            "command": "uv",
            "args": [
              "run",
              "openml-mcp-server"
            ],
            "env": {
              "OPENML_API_KEY": "YOUR_ACTUAL_OPENML_API_KEY"
            }
          }
        }
      }
      
  3. Save and Restart:

    • Save claude_desktop_config.json.
    • Completely quit and restart Claude Desktop.
  4. Verify:

    • Look for the hammer icon README image in the Claude chat input.
    • Click it to see the available "OpenML Explorer" tools (e.g., get_dataset_description, list_tasks).

Examples

  • "Show the description for OpenML dataset ID 61."
  • "List features for dataset 31."
  • "Find the first 3 classification tasks on OpenML."
  • "Get the run description for run ID 100."

Development

See the Testing Instructions below.

Running Tests

To run the test suite (requires pytest and pytest-asyncio):

uv run pytest

Contributing

We welcome contributions! Please see our Contributing Guidelines for more details.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Comments

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