AWS Strands Agents: Building And Connecting Your First Model Context Protocol (MCP) Server MCP Server

Model Context Protocol (MCP) Server and AWS Strands Agents Demonstration

Local serverstdioPython

What is the AWS Strands Agents: Building And Connecting Your First Model Context Protocol (MCP) Server MCP Server?

Model Context Protocol (MCP) Server and AWS Strands Agents Demonstration

What it actually does

The Model Context Protocol (MCP) provides a standardized interface that enables AI agents to interact seamlessly with external services. In this post, we’ll demonstrate how to build an MCP server that integrates with Shutterstock — my favorite platform for high-quality licensed images, videos, music, and creative tools — using their robust API. We’ll then show how to expose these rich media search capabilities to agents developed with Strands Agents, AWS’s code-first framework for building production-ready AI agents. By orchestrating multiple agents, we’ll enable them to access the National Weather Service (NWS)

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Maintainer setup documentation.

Configuration

  • Git distributed version control system * Node.js v22.16.01 LTS or newer (MCP servers) * npm, Yarn, or other Node.js package manager * Python 3.13.x (Strands Agents) * pip, Poetry, or another Python package manager * AWS Account (for access to Amazon Bedrock generative AI models; other model providers are also supported) * Free Shutterstock Test Account and Token (Register at Shutterstock
VariableDescriptionRequired
API_KEYCredential the server authenticates with.Yes
SHUTTERSTOCK_API_TOKENCredential the server authenticates with.Yes

Example prompts to try

  • “Use AWS Strands Agents: Building And Connecting Your First Model Context Protocol (MCP) Server to Optional.”

Frequently asked questions

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.