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prassanna-ravishankar/clearml-mcp

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17 stars 7 forks 품질 77 트렌드 25MIT

lightweight MCP server for ClearML

개요

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

원문 README의 일부입니다. 원문 보기.

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

GitHub에서 전체 README 보기

설치

uvx clearml-mcp
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설정

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