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MLflow Prompt Registry MCP Server

MLflow Prompt Registry MCP Server

Local
github.com/B-Step62AI & Agents3Updated 83w ago

About MLflow Prompt Registry MCP Server

MLflow Prompt Registry MCP Server gives MCP clients access to prompt templates stored in MLflow. It supports discovering prompts and retrieving a selected template with its variables compiled, for workflows such as repeated tasks in Claude Desktop.

Key features

  1. 01List available prompts
  2. 02Filter and paginate prompt listings
  3. 03Retrieve a named prompt
  4. 04Compile prompts with variables

Use cases

  1. 01Finding a prompt in MLflow
  2. 02Loading a template for a repeated task
  3. 03Filling prompt variables before use

MCP support

The server implements the MCP Prompts specification, exposing MLflow prompt templates through list and retrieval operations. Clients can list prompts and fetch a compiled prompt with supplied arguments.

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

MLflow Prompt Registry MCP Server

Model Context Protocol (MCP) Server for MLflow Prompt Registry, enabling access to prompt templates managed in MLflow.

This server implements the MCP Prompts specification for discovering and using prompt templates from MLflow Prompt Registry. The primary use case is to load prompt templates from MLflow in Claude Desktop, allowing users to instruct Claude conveniently for repetitive tasks or common workflows.

README image

Tools

  • list-prompts
    • List available prompts
    • Inputs:
      • cursor (optional string): Cursor for pagination
      • filter (optional string): Filter for prompts
    • Returns: List of prompt objects
  • get-prompt
    • Retrieve and compile a specific prompt
    • Inputs:
      • name (string): Name of the prompt to retrieve
      • arguments (optional object): JSON object with prompt variables
    • Returns: Compiled prompt object

Setup

1: Install MLflow and Start Prompt Registry

Install and start an MLflow server if you haven't already to host the Prompt Registry:

pip install mlflow>=2.21.1
mlflow server --port 5000
2: Create a prompt template in MLflow

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

3: Build MCP Server
npm install
npm run build
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"
      }
    }
  }
}

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

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.