Retrieval-Augmented Generation (RAG) System with Google's ADK and Qdrant MCP
This MCP enhances large language models using a retrieval-augmented approach, combining Google's Agent Development Kit (ADK) with Qdrant vector database through MCP server for precise information retrieval.
Added on:
Created by:
Apr 16 2025
This MCP enhances large language models using a retrieval-augmented approach, combining Google's Agent Development Kit (ADK) with Qdrant vector database through MCP server for precise information retrieval.
Added on:
Created by:
Apr 16 2025
Koill
Featured
What is Retrieval-Augmented Generation (RAG) System with Google's ADK and Qdrant MCP?
This MCP is a sophisticated Retrieval-Augmented Generation (RAG) system that leverages Google's Google's Agent Development Kit (ADK) alongside Qdrant vector database via MCP server. It retrieves relevant knowledge from a vector store to augment LLM responses, improving accuracy and context relevance. Suitable for building intelligent chatbots and knowledge assistants, it features document ingestion, semantic search, and an integrated web UI for, and seamless integration with various APIs, making it ideal for enterprise knowledge management, AI-driven customer support, and research applications.
Who will use Retrieval-Augmented Generation (RAG) System with Google's ADK and Qdrant MCP?
- AI developers
- Data scientists
- Knowledge engineers
- Enterprise IT teams
- Research institutions
How to use the Retrieval-Augmented Generation (RAG) System with Google's ADK and Qdrant MCP?
- Clone the repository from GitHub
- Configure environment variables and API keys
- Build and start Qdrant and MCP server using Docker Compose
- Ingest documents into the system via provided scripts
- Run the main system with default or custom settings
- Use the built-in ADK-UI for testing and debugging
Retrieval-Augmented Generation (RAG) System with Google's ADK and Qdrant MCP's Core Features & Benefits
The Core Features
- Semantic search with Qdrant vector database
- Integration with Google's Agent Development Kit (ADK)
- Model Context Protocol (MCP) server for data handling
- Document ingestion with text extraction and embedding
- Built-in web UI for testing and debugging
The Benefits
- Improves LLM accuracy with relevant retrieved context
- Seamless integration of retrieval and generation
- Supports large-scale document processing and knowledge management
- Customizable and extendable architecture
- Enhanced monitoring and debugging capabilities
Retrieval-Augmented Generation (RAG) System with Google's ADK and Qdrant MCP's Main Use Cases & Applications
- Building intelligent chatbots for customer support
- Knowledge base augmentation for enterprise data
- Research projects requiring precise information retrieval
- Automated document processing and analysis
FAQs of Retrieval-Augmented Generation (RAG) System with Google's ADK and Qdrant MCP
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