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| title: MLflow Mcp | |
| emoji: 👁 | |
| colorFrom: indigo | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 5.33.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| short_description: MCP service for MLFlow | |
| tags: | |
| - mcp-server-track | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
| # Gradio-Based MCP Service Design | |
| ## 1. Overview | |
| This is a Gradio application that exposes a set of MLflow "tools" (functions) as JSON/HTTP endpoints. An LLM (e.g., Claude or another agent) can invoke these endpoints to manage experiments, runs, and models. A minimal form-per-function UI also allows humans to issue the same commands via a Hugging Face Space. | |
| **Core functions (MCP tools):** | |
| 1. Set MLflow tracking URI | |
| 2. Get system info (including tracking URI, registry URI, MLflow version, etc.) | |
| 3. List all experiments | |
| 4. Create a new experiment | |
| 5. Register a model artifact | |
| 6. Search runs by filter | |
| 7. List all registered models | |
| 8. Get detailed info about a specific registered model | |
| ## 2. Demos | |
| Due to time and resource limitation, this demo shows a MLFLow server run locally and also the MCP server. Please input a remote MLFlow server if you would like to use the config in HuggingFace space. | |
| [Demo video in youtube](https://youtu.be/LLpXTcnpkZs) | |