What languages are available in these demos?
TypeScript, Python, Java (Spring AI), and Kotlin (Spring AI) modules are provided.
@aws-samples
基本信息
Collection of examples of how to use Model Context Protocol with AWS.
工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
A collection of sample applications demonstrating how to build Agentic AI with AWS using the Model Context Protocol (MCP). It includes multiple demo modules in TypeScript, Python, Java, and Kotlin that implement MCP clients and servers integrated with Amazon Bedrock, supporting both SSE and stdio transports, with deployment options ranging from local containers to Amazon ECS.
Browse the module table in the README to select a demo that fits your language and deployment preference. Each module directory contains its own code, configuration, and instructions for setup and execution.
TypeScript, Python, Java (Spring AI), and Kotlin (Spring AI) modules are provided.
Both SSE (Server-Sent Events) and stdio (standard input/output) transports are demonstrated.
Yes, one module (spring-ai-java-bedrock-mcp-rag) uses PostgreSQL with pgvector for RAG in a dog adoption agent.
Yes, several modules are designed to run on Amazon ECS (EC2 or Fargate) and can be exposed via an Application Load Balancer.
Yes. The "Server Client MCP/stdio Demo" module runs locally using Python and connects directly with Amazon Bedrock.
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