Overview
What is Search Engine with RAG and MCP?
This project is a powerful search engine that integrates LangChain, Model Context Protocol (MCP), and Retrieval-Augmented Generation (RAG) to create an AI system capable of searching the web and providing relevant answers.
How to use Search Engine with RAG and MCP?
To use the search engine, clone the repository, install the dependencies, and run the application in one of three modes: Direct Search, Agent Mode, or MCP Server Mode.
Key features of Search Engine with RAG and MCP?
- Web search capabilities using the Exa API
- Content retrieval using FireCrawl
- RAG for enhanced information extraction
- MCP server for standardized tool invocation
- Support for local and cloud-based LLMs
- Flexible architecture for various search modes
- Comprehensive error handling
- Asynchronous processing for efficiency
Use cases of Search Engine with RAG and MCP?
- Conducting web searches for information retrieval.
- Utilizing agent-based search for complex queries.
- Running a local MCP server for tool invocation.
FAQ from Search Engine with RAG and MCP?
- What programming language is used?
The project is developed in Python 3.13+.
- Is there a license for this project?
Yes, it is licensed under the MIT License.
- How can I contribute to the project?
You can contribute by submitting issues or pull requests on the GitHub repository.