Shutterstock Stock Photo MCP Server
Provides tools to search for stock photography based on location and conditions using the Shutterstock API.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Shutterstock Stock Photo MCP ServerShow me a stock photo that fits today's weather in Tokyo"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AWS Strands Agents: Building and Connecting Your First Model Context Protocol (MCP) Server
Overview
Deploy an MCP server that searches for stock photography based on your current location and conditions using third-party APIs, and orchestrate it with Strands Agents and the Amazon Q Developer CLI.
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) API, intelligently select contextually relevant photos based on current weather conditions, and deliver results that showcase the power of reasoning and context-aware automation.
JavaScript/Node.js MCP Servers based on: https://github.com/lucianoayres/mcp-server-node.
Related MCP server: tes-mcp-server
Prerequisites
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 Developers)
Optional: Amazon Q Developer CLI for last section of post
Installation
Clone Repository and Install Packages
npm install -g corepack # if using yarn
git clone https://github.com/garystafford/aws-strands-agents-mcp-demo.git
cd aws-strands-agents-mcp-demo
yarn installStart MCP Servers
# terminal window 1: STDIO transport
# environment variables are set by MCP server with STDIO
export API_KEY=abc-1234567890
export SHUTTERSTOCK_API_TOKEN=<YOUR_SHUTTERSTOCK_API_TOKEN>
node mcp-server.js
# terminal window 2: Streamable HTTP transport
# environmental variables are set by agent with Streamable HTTP
node mcp-server-remote.jsInstall Strands Agents
python -m pip install virtualenv -Uqqq
python -m venv .venv
source .venv/bin/activate
python -m pip install pip -Uqqq
python -m pip install -r requirements.txt -UqqqStart Strands Agents
export API_KEY=abc-1234567890
export SHUTTERSTOCK_API_TOKEN=<YOUR_SHUTTERSTOCK_API_TOKEN>
python agent_stdio_multi_agent.pyThe contents of this repository represent my viewpoints and not of my past or current employers, including Amazon Web Services (AWS). All third-party libraries, modules, plugins, and SDKs are the property of their respective owners.
This server cannot be deployed
Maintenance
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