ClearML MCP Server is a lightweight Model Context Protocol server that enables AI assistants to access and analyze ClearML data during conversations. It exposes a comprehensive set of MCP-compatible tools to discover experiments across projects, view model metadata, retrieve artifacts, and analyze performance. The server supports task operations (get_task_info, list_tasks, get_task_parameters, get_task_metrics, get_task_artifacts), model operations (get_model_info, list_models, get_model_artifacts), and project operations (list_projects, get_project_stats, find_project_by_pattern, find_experiment_in_project), along with analysis utilities (compare_tasks, search_tasks). It also offers real-time access to training scalars, validation curves, and convergence insights, enabling contextual decision-making. The MCP server is cross-platform and designed to work with major AI assistants and editors, including Claude Desktop, Cursor, Continue, Cody, and other MCP-enabled applications. Typical usage involves configuring ClearML credentials, starting the MCP server via uvx clearml-mcp or running it with Python, and issuing natural-language prompts like “Show the latest experiments in project X” or “Compare performance metrics between two tasks.” The README provides setup, integration examples, troubleshooting, and development commands to run tests and demos.