Manages environment variables including API keys and database paths for secure configuration
Implements document embedding, indexing, and semantic search capabilities to enable RAG (Retrieval-Augmented Generation) functionality
Leverages OpenAI models for context-aware response generation and text processing within the RAG implementation
RAG Information Retriever
A powerful MCP server that implements Retrieval-Augmented Generation (RAG) to efficiently retrieve and process important information from various sources. This server combines the strengths of retrieval-based and generation-based approaches to provide accurate and contextually relevant information.
Features
- Intelligent Information Retrieval
- Semantic search capabilities
- Context-aware information extraction
- Relevance scoring and ranking
- Multi-source data integration
- RAG Implementation
- Document embedding and indexing
- Query understanding and processing
- Context-aware response generation
- Knowledge base integration
- Advanced Processing
- Text chunking and processing
- Semantic similarity matching
- Context window management
- Response synthesis
Setup
- Environment Configuration
Create a
.env
file with the following variables: - Dependencies
Usage
Basic Information Retrieval
Advanced Retrieval
Architecture
How It Works
- Query Processing
- Input query is received and preprocessed
- Query intent is analyzed
- Relevant context is identified
- Information Retrieval
- Vector similarity search is performed
- Relevant documents are retrieved
- Context is assembled and ranked
- Response Generation
- Retrieved information is processed
- Response is generated with context
- Results are formatted and returned
Performance Features
- Efficient vector search
- Caching of frequent queries
- Batch processing capabilities
- Asynchronous operations
Security
- Input sanitization
- Rate limiting
- Access control
- Data encryption
Running the Server
To start the MCP server in development mode:
Error Handling
The system provides comprehensive error handling for:
- Invalid queries
- Missing context
- Database connection issues
- API rate limits
- Processing errors
Best Practices
- Query Formulation
- Be specific in your queries
- Provide relevant context
- Use appropriate filters
- Context Management
- Keep context windows focused
- Update knowledge base regularly
- Monitor relevance scores
Contributing
Feel free to submit issues and enhancement requests!
Security Notes
- API keys should be kept secure
- Regular security audits
- Data privacy compliance
- Access control implementation
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.
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