prassanna-ravishankar/clearml-mcp

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lightweight MCP server for ClearML

Обзор

A lightweight that enables AI assistants to interact with ClearML experiments, models, and projects. Get comprehensive ML experiment context and analysis directly in your AI conversations. - : Find and analyze ML experiments across projects - : Compare model metrics and training progress - : Access training scalars, validation curves, and convergence analysis - : Filter tasks by name, tags, status, and custom queries - : Retrieve model files, datasets, and experiment outputs - : Works with all major AI assistants and code editors - (installation guide) for uvx command - with valid API credentials in ~/.clearml/clearml.conf You need a configured ClearML environment with your credentials in ~/.clearml/clearml.conf: Get your credentials from ClearML Settings. Add to your Claude Desktop configuration: : ~/Library/Application Support/Claude/claude_desktop_config.json : %APPDATA%/Claude/claude_desktop_config.json Add to your Cursor settings (Ctrl/Cmd + , → Search "MCP"):

README

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ClearML MCP Server

A lightweight Model Context Protocol (MCP) server that enables AI assistants to interact with ClearML experiments, models, and projects. Get comprehensive ML experiment context and analysis directly in your AI conversations.

✨ Features

🔍 Experiment Discovery: Find and analyze ML experiments across projects
📊 Performance Analysis: Compare model metrics and training progress
📈 Real-time Metrics: Access training scalars, validation curves, and convergence analysis
🏷️ Smart Search: Filter tasks by name, tags, status, and custom queries
📦 Artifact Management: Retrieve model files, datasets, and experiment outputs
🌐 Cross-platform: Works with all major AI assistants and code editors

📋 Requirements

uv (installation guide) for uvx command
ClearML account with valid API credentials in ~/.clearml/clearml.conf

🚀 Quick Start

Prerequisites

You need a configured ClearML environment with your credentials in ~/.clearml/clearml.conf:

[api]
api_server = https://api.clear.ml
web_server = https://app.clear.ml
files_server = https://files.clear.ml
credentials {
    "access_key": "your-access-key",
    "secret_key": "your-secret-key"
}

Get your credentials from ClearML Settings.

Installation

# Install from PyPI
pip install clearml-mcp

# Or run directly with uvx (no installation needed)
uvx clearml-mcp

🔌 Integrations

Открыть полный README на GitHub

Установка

uvx clearml-mcp

Новичок в MCP? Начните с руководства на mcpskill.org →

Конфигурация

{
  "mcpServers": {
    "clearml": {
      "command": "uvx",
      "args": ["clearml-mcp"]
    }
  }
}