prassanna-ravishankar/clearml-mcp

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:
Get your credentials from ClearML Settings.
Installation
🔌 Integrations
🤖 Claude Desktop
Add to your Claude Desktop configuration:
**macOS**: ~/Library/Application Support/Claude/claude_desktop_config.json
**Windows**: %APPDATA%/Claude/claude_desktop_config.json
Alternative with pip installation:
⚡ Cursor
Add to your Cursor settings (Ctrl/Cmd + , → Search "MCP"):
Or add to .cursorrules in your project:
🔥 Continue
Add to your Continue configuration (~/.continue/config.json):
🦾 Cody
Add to your Cody settings:
🧠 Other AI Assistants
For any MCP-compatible AI assistant, use this configuration:
**Compatible with:**
- Zed Editor
- OpenHands
- Roo-Cline
- Any MCP-enabled application
🛠️ Available Tools
The ClearML MCP server provides **14 comprehensive tools** for ML experiment analysis:
📊 Task Operations
- get_task_info - Get detailed task information, parameters, and status
- list_tasks - List tasks with advanced filtering (project, status, tags, user)
- get_task_parameters - Retrieve hyperparameters and configuration
- get_task_metrics - Access training metrics, scalars, and plots
- get_task_artifacts - Get artifacts, model files, and outputs
🤖 Model Operations
- get_model_info - Get model metadata and configuration details
- list_models - Browse available models with filtering
- get_model_artifacts - Access model files and download URLs
📁 Project Operations
- list_projects - Discover available ClearML projects
- get_project_stats - Get project statistics and task summaries
- find_project_by_pattern - Find projects matching name patterns
- find_experiment_in_project - Find specific experiments within projects
🔍 Analysis Tools
- compare_tasks - Compare multiple tasks by specific metrics
- search_tasks - Advanced search by name, tags, comments, and more
💡 Usage Examples
Demo
Once configured, you can ask your AI assistant questions like:
- *"Show me the latest experiments in the 'computer-vision' project"*
- *"Compare the accuracy metrics between tasks task-123 and task-456"*