Multi-Protocol RAG Server (MCP + A2A)
Advanced implementation of a Retrieval Augmented Generation (RAG) server that supports both Model Context Protocol (MCP) and Google A2A protocols. This dual-protocol architecture enables flexible integration with different AI systems while maintaining a unified RAG backend.
A2AJava is swiss knife of agentic applications in Java and Kotlin. It supports multiple protocols including Google A2A, MCP, and others. This project demonstrates how to build a powerful RAG search application that integrates Google's Agent-to-Agent (A2A) protocol with Spring Boot and MongoDB Atlas.
Architecture Overview
The server implements a unique dual-protocol approach:
- MCP (Model Context Protocol) - Enables direct communication with MCP-compatible AI models
- A2A (Agent-to-Agent Java) - Provides Java-based agent communication capabilities
This architecture allows for:
- Seamless integration with multiple AI protocols
- Unified RAG backend serving different client types
- Flexible deployment options
- Protocol-specific optimizations
Screenshots and Features
A2A Protocol Integration
Agent Chat Interface
A2A protocol enabling agent-to-agent communication
Agent Events
Event handling in the A2A protocol implementation
Agent Addition
Interface for adding new agents to the system
MCP Protocol Integration
Claude MCP Agent
MCP protocol integration with Claude AI
MCP Conversation Flow
Demonstration of MCP-based conversation flow
RAG Retrieval Process
RAG retrieval process using the MCP protocol
Key Components
A2ARagService: Handles A2A protocol-specific RAG operationsRagRetrivalController: Manages RAG retrievals across both protocolsYardShareA2ACardController: Controls A2A-specific card interactionsRAGConfiguration: Configures RAG settings for both protocols
Building and Running
To build the project:
mvn clean install
To run the server:
java -jar target/mcp-rag.jar
Configuration
The server can be configured through:
application.yml: Main application configurationtools4ai.properties: AI-specific settings
Benefits of Dual-Protocol Architecture
- Protocol Flexibility: Support for both MCP and A2A allows integration with a wider range of AI systems
- Unified RAG Backend: Single source of truth for knowledge retrieval
- Scalable Design: Easy to add support for additional protocols
- Optimized Performance: Protocol-specific optimizations while maintaining a common core
License
See LICENSE file for details.
