What does SwarmUI_MCP_Agent do?
It acts as a bridge between an LLM agent (running on Ollama) and the SwarmUI image generation API. The agent receives a text prompt, calls the SwarmUI `/GenerateText2Image` endpoint, and returns the generated image.
@MathewTomberlin
基本情報
A simple prototype SwarmUI MCP server with accompanying local LangChain Ollama agent
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SwarmUI_MCP_Agent is a prototype MCP (Model Context Protocol) server that integrates with SwarmUI's local API and a LangChain Ollama agent. It exposes SwarmUI's /GenerateText2Image and /GetNewSession endpoints as tools, allowing an LLM agent to generate images from text prompts. The server is built with Node.js, TypeScript, Express, and Axios, while the agent uses Python, LangChain, and Ollama.
From the SwarmUI_MCP_Agent/src directory, run tsc server.ts && node server.js to start the MCP server. Then ensure SwarmUI is running, and from the root directory run python run.py to launch the Streamlit UI. In the UI, enter the SwarmUI port, select an LLM model, type an image prompt, and click submit.
It acts as a bridge between an LLM agent (running on Ollama) and the SwarmUI image generation API. The agent receives a text prompt, calls the SwarmUI `/GenerateText2Image` endpoint, and returns the generated image.
You need Node.js, npm, Python, pip, and an Ollama installation with a model (e.g., dolphin‑mistral). SwarmUI must be running locally.
The MCP server creates an Axios HTTP client that sends POST requests to the SwarmUI API on localhost (default port configurable in code). No authentication is mentioned.
The prototype only exposes the `/GenerateText2Image` endpoint. The model and port are hardcoded and must be changed manually. The agent has a `max_iterations` of 1, and Pydantic input validation is not yet fully functional for multiple inputs.
Images are saved in SwarmUI's `/Output` directory and can also be viewed in SwarmUI's Image History.

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