Mcp Openvto MCP Server

<a href='https://github.com/nkapila6/mcp-openvto/'><img src='https://github.com/user-attachments/assets/23d6b7fa-5037-4090-990a-b289140bece5' width='200' height='200'></a> # mcp-openvto MCP SSE server that allows you to do Virtual Try-On through LLM Chat using a back-end db hosted locally or through the cloud (Couchbase) and Replicate APIs. ## Attribution The MCP server uses the following services / libraries. - [cpp-mcp](https://github.com/hkr04/cpp-mcp/): C++ MCP Client and Server library. - [Eigen C++ library](https://eigen.tuxfamily.org/index.php?title=Main_Page): C++ mathematical linear algebra library. - [Ollama](https://github.com/jmont-dev/ollama-hpp): C++ bindings for Ollama API. - [Couchbase] (optional) ## Requirements - The .CSV file in the `db` folder (required if not using Couchbase) - CSV files alongside embeddings uploaded to Couchbase (local) or Couchbase Capella (Cloud). Works on free tier! - Ollama - ... coming soon... ## Configuration Coming soon ## Why C++? I already built 2 MCP servers in Python before and the dependencies and Docker image sizes were too huge. Yes, I could have used an easier example like GoLang but I thought why not! This project taught me how much I take Python abstractions for granted. 💀 C/C++ humbles you that way. And yes, doing it in C++ was advantageous. <img width="263" alt="image" src="https://github.com/user-attachments/assets/9e70c769-b096-4a4c-88e6-0d66e9423730" /> ## Example inferences ### Basic example A basic example using Couchbase (Cloud) services. https://github.com/user-attachments/assets/30166f61-3b60-4890-b3c9-7ccf5c1c3f32 ### Regressive inference (Experimental) An example of a regressive inference using the MCP server with Couchbase (Cloud) services. Regressive here means you can use previous output as the base image to virtual transfer on, e.g. T-Shirt Try On -> Pant Try On using T-Shirt Try On Image. https://github.com/user-attachments/assets/cc85c216-99ec-4aff-a583-48b7735dbcaf ### Meme-ing