Agentic AI Demos
Provides example implementations for building agentic AI solutions with AWS, utilizing the Model Context Protocol.
About
This collection offers various practical examples demonstrating how to construct Agentic AI applications using AWS services, specifically focusing on the Model Context Protocol (MCP). It includes diverse configurations, such as client-server interactions over SSE and stdio, deployments on Amazon ECS, and integrations with technologies like Spring AI, FastAPI, Anthropic Bedrock, and pgVector for RAG capabilities.
Key Features
- Spring AI Agent and MCP Server examples running on ECS
- Full client-server MCP/SSE demo deployable in Docker containers
- 59 GitHub stars
- Local MCP/stdio client-server demo for Python
- Bedrock Converse Client with pgVector RAG and Spring AI MCP Server
- FastAPI client with Anthropic Bedrock and MCP SSE Server on ECS Fargate
Use Cases
- Developing agentic AI applications with Amazon Bedrock
- Integrating RAG (Retrieval Augmented Generation) into agentic AI workflows
- Learning and implementing the Model Context Protocol (MCP) on AWS
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