@ProbonoBonobo
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"sui-mcp-server": {
"command": "pipx",
"args": [
"ensurepath"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
A proof-of-concept Machine Conversation Protocol (MCP) server that allows an AI agent to query a FAISS vector database and retrieve relevant documents for Retrieval-Augmented Generation (RAG). It integrates FastAPI, FAISS, GitHub Move file extraction, and LLM support, targeting developers building RAG workflows.
Install with pipx (pipx install -e .) or manually (pip install -r requirements.txt). Then use CLI commands like mcp-download, mcp-search-index, mcp-index, mcp-query, mcp-rag, and mcp-server. Optionally set GITHUB_TOKEN and OPENAI_API_KEY in .env. Start the server with mcp-server or python main.py, then query via MCP API at /mcp/action.
The server requires Python 3 and dependencies listed in `requirements.txt`, including FAISS, FastAPI, and an LLM provider (OpenAI or others). A GitHub token is optional for higher API rate limits.
1. User submits a question. 2. System retrieves relevant documents from the FAISS vector database. 3. Retrieved documents are formatted into a context prompt. 4. The prompt is sent to an LLM for an enhanced answer. 5. The LLM’s response is returned to the user.
The FAISS index is saved to `data/faiss_index.bin` by default, and the downloaded Move files go into `docs/move_files/`. You can customize the index path and document directory with command-line options.
Add authentication and security, support more document types, integrate with other LLM providers, improve Move parsing, and add monitoring/logging as described in the Extended section of the README.
MIT license.
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