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sample-agentic-ai-demos

by aws-samples·101·Score 46

AWS collection of MCP examples demonstrating client-server interactions with AWS services.

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Overview

This is a well-maintained collection of practical examples demonstrating how to implement MCP servers and clients with AWS services. The repository includes multiple modules showcasing different communication patterns (SSE and stdio) and deployment options (local and ECS). Each module provides clear implementations with specific use cases like RAG with pgVector and adoption appointment management.

Try asking AI

After installing, here are 5 things you can ask your AI assistant:

you:Building MCP servers on AWS infrastructure (ECS) for production deployments
you:Creating MCP clients that interact with AWS Bedrock for agentic AI applications
you:Implementing RAG systems using MCP to manage external data sources
you:What AWS services are used in these examples?
you:Can these examples be adapted for non-AWS environments?

When to choose this

When you're looking for reference implementations of MCP servers on AWS infrastructure.

When NOT to choose this

When you need a ready-to-use MCP server rather than implementation examples.

Comparable tools

mcp-server-examplesaws-bedrock-mcpaws-bedrock-agent

Installation

These examples have varying installation requirements based on the specific module. Generally, they require:

  1. AWS account with necessary permissions
  2. Docker (for containerized examples)
  3. Python 3.7+ or Java/Kotlin for respective modules

For Claude Desktop integration, you would add to config.json:

{
  "mcpServers": {
    "aws-mcp-demo": {
      "command": "python",
      "args": ["path/to/mcp/server.py"]
    }
  }
}

FAQ

What AWS services are used in these examples?
The examples primarily use Amazon Bedrock for model access and ECS for deployment infrastructure.
Can these examples be adapted for non-AWS environments?
While designed for AWS, the core MCP patterns demonstrated could be adapted to other cloud providers with modifications.

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