What does the RAG Application do?
It is a demo of Retrieval-Augmented Generation that uses an MCP server to answer questions about a company by retrieving relevant documents and generating context‑aware responses.
@hulk-pham
基本信息
A demo of Retrieval-Augmented Generation (RAG) application with MCP server integration.
工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
RAG Application is a demo of Retrieval-Augmented Generation (RAG) that integrates an MCP server. It retrieves relevant documents using vector search with ChromaDB, builds context-aware prompts, and sends them to an LLM API to answer questions about a company.
Install dependencies with pip install -r requirements.txt, set the OPENAI_API_KEY in a .env file, then connect the MCP server via Claude Desktop, Cursor, or another compatible IDE. Use the process_query tool to ask questions about the company.
It is a demo of Retrieval-Augmented Generation that uses an MCP server to answer questions about a company by retrieving relevant documents and generating context‑aware responses.
Run `pip install -r requirements.txt` in the project directory to install all dependencies.
Create a `.env` file and set your `OPENAI_API_KEY` to authenticate with the LLM API.
Connect the MCP server to a supported client (Claude Desktop, Cursor, etc.) and use the `process_query` tool to ask questions about the company.
The MCP server can be connected with Claude Desktop, Cursor, or any other IDE that supports the Model Context Protocol.

Mess in, magic out: pour in your D&D and TTRPG notes and LoreKeeper keeps them as a private store for your world. Ask Claude or ChatGPT about it, or build a sourcebook.

Sooveryn gives Claude Code a team of AI personas that remembers your project. Soov, the partner and team lead, keeps your decisions and how you work in a lasting memory, and finds them again by words and by meaning, from

MCP connector for Snipara, the Project Brain for AI coding agents

One permissioned folder your team and your AI agents both log into.
Person-owned, portable AI memory served over MCP. Your knowledge, preferences, and decisions — captured in one assistant, available in all of them.
评论