# tiny-agents [tiny-agents](https://huggingface.co/blog/python-tiny-agents) offers a minimal pattern for building tool-using agents. A small Python loop connects an MCP client to tools from MCP servers. Hugging Face Spaces work as MCP servers. Find more compatible Spaces on the [Hub](https://huggingface.co/spaces?filter=mcp-server). Create a config file that points to your local model and the tool server. This example uses an image generation [Space](https://evalstate-flux1-schnell.hf.space/). ```json { "model": "Menlo/Jan-nano", "endpointUrl": "http://localhost:8000", "servers": [ { "type": "sse", "url": "https://evalstate-flux1-schnell.hf.space/gradio_api/mcp/sse" } ] } ``` Run the agent with your config. ```bash tiny-agents run path/to/your/config.json ``` Ensure `transformers serve` is running in the background. The agent will use your local model to run the image generation tool. ```bash Agent loaded with 1 tools: • flux1_schnell_infer » Generate an image of a cat on the moon flux1_schnell_infer {"prompt": "a cat on the moon", "seed": 42, "randomize_seed": true, "width": 1024, "height": 1024, "num_inference_steps": 4} Tool req_0_tool_call [Binary Content: Image image/webp, 57732 bytes] The task is complete and the content accessible to the User Image URL: https://evalstate-flux1-schnell.hf.space/gradio_api/file=/tmp/gradio/3dbddc0e53b5a865ed56a4e3dbdd30f3f61cf3b8aabf1b456f43e5241bd968b8/image.webp 380576952 I have generated an image of a cat on the moon using the Flux 1 Schnell Image Generator. The image is 1024x1024 pixels and was created with 4 inference steps. Let me know if you would like to make any changes or need further assistance! ```