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mlflowAgent

Source

mcp server for mlflow

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Overview

mlflowAgent is a server designed to facilitate the use of MLflow, a popular platform for managing the machine learning lifecycle.

To use mlflowAgent, set up the server by following the installation instructions on the GitHub repository, and then connect it to your MLflow projects to manage experiments and models.

  • Integration with MLflow for seamless experiment tracking - Support for managing machine learning models - Easy setup and configuration for developers
  1. Tracking machine learning experiments in real-time.
  2. Managing and deploying machine learning models efficiently.
  3. Collaborating on ML projects with team members.

Add to your AI client

Use these steps to connect mlflowAgent in Cursor, Claude, VS Code, and other MCP-compatible apps. The same JSON appears in the Use with menu above for one-click copy.

Cursor

Add this to your .cursor/mcp.json file in your project root, then restart Cursor.

.cursor/mcp.json

{
  "mcpServers": {
    "mlflowagent-irahulpandey": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mlflowagent-irahulpandey"
      ]
    }
  }
}

Claude Desktop

Add this server entry to the mcpServers object in your Claude Desktop config, then restart the app.

~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)

{
  "mcpServers": {
    "mlflowagent-irahulpandey": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mlflowagent-irahulpandey"
      ]
    }
  }
}

Claude Code

Add this to your project's .mcp.json file. Claude Code will detect it automatically.

.mcp.json (project root)

{
  "mcpServers": {
    "mlflowagent-irahulpandey": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mlflowagent-irahulpandey"
      ]
    }
  }
}

VS Code (Copilot)

Add this to your .vscode/mcp.json file. Requires the GitHub Copilot extension with MCP support enabled.

.vscode/mcp.json

{
  "servers": {
    "mlflowagent-irahulpandey": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mlflowagent-irahulpandey"
      ]
    }
  }
}

Windsurf

Add this to your Windsurf MCP config file, then restart Windsurf.

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "mlflowagent-irahulpandey": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mlflowagent-irahulpandey"
      ]
    }
  }
}

Cline

Open Cline settings, navigate to MCP Servers, and add this server configuration.

Cline MCP Settings (via UI)

{
  "mcpServers": {
    "mlflowagent-irahulpandey": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mlflowagent-irahulpandey"
      ]
    }
  }
}

FAQ

What is MLflow?

MLflow is an open-source platform for managing the end-to-end machine learning lifecycle.

Is mlflowAgent free to use?

Yes! mlflowAgent is open-source and free to use for everyone.

How do I contribute to mlflowAgent?

You can contribute by submitting issues or pull requests on the GitHub repository.

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