What are the prerequisites?
You need Git, Node.js v22.16.01+, npm/Yarn, Python 3.13.x, a pip/Poetry package manager, an AWS account (for Amazon Bedrock), and a free Shutterstock test account with an API token.
@garystafford
基本情報
Model Context Protocol (MCP) Server and AWS Strands Agents Demonstration
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"aws-strands-agents-mcp-demo": {
"command": "node",
"args": [
"mcp-server.js"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
This demo project deploys an MCP server that searches for stock photography from Shutterstock based on your location and current weather conditions, then orchestrates it with Strands Agents and the Amazon Q Developer CLI. It is intended for developers building production-ready AI agents that interact with external APIs through the Model Context Protocol.
Clone the repository, install Node.js packages with yarn install, set environment variables (API_KEY and SHUTTERSTOCK_API_TOKEN), start the MCP server (either node mcp-server.js for STDIO or node mcp-server-remote.js for Streamable HTTP transport), create a Python virtual environment, install Python dependencies, and run the agent with python agent_stdio_multi_agent.py.
You need Git, Node.js v22.16.01+, npm/Yarn, Python 3.13.x, a pip/Poetry package manager, an AWS account (for Amazon Bedrock), and a free Shutterstock test account with an API token.
The MCP server supports both STDIO transport (via `mcp-server.js`) and Streamable HTTP transport (via `mcp-server-remote.js`).
Register for a free Shutterstock Test Account at the Shutterstock Developers portal to get your API token.
The AWS account provides access to Amazon Bedrock generative AI models; other model providers are also supported.
The MCP servers are written in JavaScript (Node.js), and the Strands Agents orchestration is written in Python.
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