This MCP demonstrates a Retrieval-Augmented Generation (RAG) application that integrates MCP server functionality, document retrieval via vector search, and LLM API connection. It allows context-aware question answering and document processing, making it suitable for knowledge management, research assistance, and intelligent chatbot development.
Added on:
Created by:
Apr 08 2025
This MCP demonstrates a Retrieval-Augmented Generation (RAG) application that integrates MCP server functionality, document retrieval via vector search, and LLM API connection. It allows context-aware question answering and document processing, making it suitable for knowledge management, research assistance, and intelligent chatbot development.
Added on:
Created by:
Apr 08 2025
Hulk Pham
Featured
What is Retrieval-Augmented Generation (RAG) with MCP Server?
This MCP provides a comprehensive retrieval-augmented generation solution by combining document retrieval through vector search with ChromaDB, context management, and prompt construction with LLM APIs. The system connects to an MCP server, enabling efficient document handling, context-aware prompt generation, and improved accuracy in responses. It supports applications like knowledge bases, research tools, and AI chatbots that require integrating external data with language models for accurate and contextually relevant outputs.
Who will use Retrieval-Augmented Generation (RAG) with MCP Server?
- AI Researchers
- Developers
- Knowledge Workers
- Chatbot Developers
- Data Scientists
How to use the Retrieval-Augmented Generation (RAG) with MCP Server?
- Step1: Clone the repository from GitHub
- Step2: Install dependencies with 'pip install -r requirements.txt'
- Step3: Configure environment variables in .env file, including OPENAI_API_KEY
- Step4: Connect to MCP server via preferred IDE or tool
- Step5: Use process_query tool to ask questions or process documents
Retrieval-Augmented Generation (RAG) with MCP Server's Core Features & Benefits
The Core Features
- MCP server integration
- Document retrieval with ChromaDB
- Context-aware prompt generation
- LLM API integration
The Benefits
- Enhanced document retrieval accuracy
- Contextually relevant responses
- Seamless integration with MCP infrastructure
- Supports knowledge management and AI research
Retrieval-Augmented Generation (RAG) with MCP Server's Main Use Cases & Applications
- Knowledge base question answering
- Research assistance
- Document processing and retrieval
- Intelligent chatbot development
FAQs of Retrieval-Augmented Generation (RAG) with MCP Server
Developer
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