B Step62 MCP Server Mlflow

🚀 MLflow Prompt Registry MCP Server

The Model Context Protocol (MCP) server enables access to prompt templates managed in MLflow for MLflow Prompt Registry.

This server implements the MCP Prompts specification to discover and use prompt templates hosted in MLflow. The primary use case is to load prompt templates from MLflow into Claude Desktop, allowing users to conveniently instruct Claude to perform repetitive tasks or common workflows.

🚀 Quick Start

✨ Features

• list-prompts:
  • Lists available prompts.
  • Input:
    • cursor (optional string): Pagination cursor.
    • filter (optional string): Prompt filter.
  • Return: A list of prompt objects.
• get-prompt:
  • Retrieves and compiles a specific prompt.
  • Input:
    • name (string): Name of the prompt to retrieve.
    • arguments (optional object): JSON object containing prompt variables.
  • Return: A compiled prompt object.

📦 Installation

Step 1: Install MLflow and Start Prompt Registry

If not already installed, install and start MLflow to host the Prompt Registry:

pip install mlflow>=2.21.1
mlflow server --port 5000

Step 2: Create a Prompt Template in MLflow

If you haven't already, follow this guide to create a prompt template in MLflow.

Step 3: Build the MCP Server

npm install
npm run build

Step 4: Add the Server to Claude Desktop

Configure Claude for Desktop by editing claude_desktop_config.json:

{
  "mcpServers": {
    "mlflow": {
      "command": "node",
      "args": ["<absolute-path-to-this-repository>/dist/index.js"],
      "env": {
        "MLFLOW_TRACKING_URI": "http://localhost:5000"
      }
    }
  }
}

⚠️ Important Note

Make sure to replace MLFLOW_TRACKING_URI with the actual address of your MLflow server.