CDM MCP Server

Name: CDM MCP Server
Author: kbase

@kbase

Repository

About CDM MCP Server

No overview available yet

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "cdm-mcp-server": {
      "command": "docker",
      "args": [
        "network",
        "create",
        "cdm-jupyterhub-network"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is CDM MCP Server?

A FastAPI-based service that implements the Model Context Protocol (MCP) to enable AI assistants to interact with Delta Lake tables stored in MinIO through Spark. It is intended for local development or evaluation only and is not approved for production deployment.

How to use CDM MCP Server?

Clone the repository, create required directories, set up a Docker network, and start the services with docker-compose up -d --build. Then access the MCP server at http://localhost:8000/docs. For AI assistant integration, configure an mcp.json file and set up an MCP host.

Key features of CDM MCP Server

Read-oriented queries against Delta Lake tables via natural language
Integration with MinIO object storage and Spark
Implements the Model Context Protocol for AI assistants
Quick local setup using Docker Compose
Includes sample data creation and API usage examples
Supports JupyterHub and Spark Master UI

Use cases of CDM MCP Server

AI assistants querying Delta Lake tables stored in MinIO
Local development and evaluation of MCP-based data interactions
Prototyping natural language data operations with Spark

FAQ from CDM MCP Server

What does CDM MCP Server do?

It allows AI assistants to execute read-oriented queries against Delta Lake tables stored in MinIO through Spark, following the Model Context Protocol.

Is CDM MCP Server approved for production?

No. The README explicitly states it is not approved for deployment to any production environment, including CI, without explicit approval from KBase leadership.

What are the runtime requirements?

Docker, Docker Compose, and a local network (cdm-jupyterhub-network). The service runs locally via docker-compose up.

Where does data live?

Data is stored in MinIO (object storage) and accessed via Spark. The service creates a local shared workspace directory (cdr/cdm/jupyter/cdm_shared_workspace).