MCP Rag

The project aims to connect RAG applications to open-webui through the MCP protocol to achieve model context interaction, including basic PoC verification, knowledge base integration, and client docking.

Artificial intelligence chatbots Knowledge management and memory #RAG Integration #MCP Protocol #Knowledge Base #Model Interaction .Python

rating : 2.5 points

downloads : 20

update time : 2025-04-28

What is the MCP RAG Server?

The MCP RAG Server is an implementation of the Model Context Protocol (MCP) for connecting Retrieval Augmented Generation (RAG) applications to Open-WebUI. It makes AI responses more context-aware and supports more complex interactions.

Key Features

Through the MCP protocol, RAG applications can be seamlessly integrated with Open-WebUI to provide a smarter conversation experience. The server supports multiple RAG architectures and allows for custom knowledge base connectors.

Application Scenarios

The MCP RAG Server is suitable for AI application scenarios that require context awareness, such as intelligent customer service, chatbots, and question-answering systems. It is particularly suitable for handling complex queries and multi-turn conversations.

Features

Based on the MCP ProtocolAchieves compatibility with Open-WebUI and supports standardized context interactions.

Flexible Knowledge Base ConnectorAllows users to customize the knowledge base and supports multiple storage and retrieval methods.

High EfficiencyOptimizes the execution efficiency of the RAG architecture and reduces response latency.

Advantages and Disadvantages

How to Use

Install dependencies: Ensure that Python and related libraries are installed.

Configure the knowledge base: Create or select a knowledge base and define the connector.

Start the server: Run the MCP RAG Server and integrate it with Open-WebUI.

Usage Examples

Frequently Asked Questions

Troubleshooting

Unable to connect to the knowledge base? Check the network configuration and connector implementation.

Long response time? Optimize the query algorithm or increase resource allocation.

Related Resources

Official documentation and usage guide.

Open-source implementation and example code.

🚀 Open Source Project: Connecting RAG Applications to open-webui Using MCP

This project aims to connect RAG applications to open-webui using the Model Context Protocol (MCP). It includes basic concept verification, implementation of a simple knowledge base, and integration of the MCP client with open-webui.

🚀 Quick Start

🔍 Basic MCP Proof of Concept (Hello World)

pip install mcp[cli]

Look for documentation related to SSE code snippets.
Run the server using uvicorn.
The initial attempt failed. After checking the documentation of the SseServerTranpsort class, it was found that it differed from the description on the official MCP website.
Changed Route to Mount, and the problem was solved.
The Starlette framework caused a 307 temporary redirect error. When testing with curl, it was found that this was due to the lack of a trailing slash.
By checking the GitHub repository, it was found that all routes in the server code end with a trailing slash, especially the part sse = SseServerTransport("/messages/"), which tells the client the endpoint to call.
Added some prompts and checked the client.

📚 Project Description

I wanted to try the Model Context Protocol because I've been working on a RAG prototype for open-webui. MCP seems similar to LSP. Since the server and client are not on the same machine, we have to use SSE transport.
The official MCP documentation has some code snippets, and I had to adjust them according to the docstrings in the mcp Python library. It took a lot of time to solve the problems. Initially, there was a 307 temporary redirect error because the server sent the wrong endpoint.
Test! Build a simple REPL to interact with the server.