AWS MCP Servers — specialized MCP servers that bring AWS best practices directly to your development workflow
A suite of specialized MCP servers that help you get the most out of AWS, wherever you use MCP.
This monorepo contains the following MCP servers:
A server for managing and coordinating other AWS Labs MCP servers.
A server for accessing AWS documentation and best practices.
A server for accessing Amazon Bedrock Knowledge Bases.
A server for AWS CDK best practices.
A server for AWS Cost Analysis.
A server for generating images using Amazon Nova Canvas.
The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.
AWS MCP Servers use this protocol to provide AI applications access to AWS documentation, contextual guidance, and best practices. Through the standardized MCP client-server architecture, AWS capabilities become an intelligent extension of your development environment or AI application.
For example, you can use the AWS Documentation MCP Server to help your AI assistant research and generate code for any AWS service, like Amazon Bedrock Inline agents. Alternatively, you could use the CDK MCP Server to have your AI assistant create infrastructure-as-code implementations that use the latest AWS CDK APIs and follow AWS best practices.
AWS MCP servers enable enhanced cloud-native development, infrastructure management, and development workflows—making AI-assisted cloud computing more accessible and efficient.
The Model Context Protocol is an open source project run by Anthropic, PBC. and open to contributions from the entire community.
Each server has specific installation instructions. Generally, you can:
uv from Astraluv python install 3.10Example configuration for Amazon Q CLI MCP (~/.aws/amazonq/mcp.json):
{
"mcpServers": {
"awslabs.core-mcp-server": {
"command": "uvx",
"args": ["awslabs.core-mcp-server@latest"],
"env": {
"FASTMCP_LOG_LEVEL": "ERROR",
"MCP_SETTINGS_PATH": "path to your mcp settings file"
}
},
"awslabs.nova-canvas-mcp-server": {
"command": "uvx",
"args": [
"awslabs.nova-canvas-mcp-server@latest"
],
"env": {
"AWS_PROFILE": "your-aws-profile",
"AWS_REGION": "us-east-1",
"FASTMCP_LOG_LEVEL": "ERROR"
}
},
"awslabs.bedrock-kb-retrieval-mcp-server": {
"command": "uvx",
"args": ["awslabs.bedrock-kb-retrieval-mcp-server@latest"],
"env": {
"AWS_PROFILE": "your-aws-profile",
"AWS_REGION": "us-east-1",
"FASTMCP_LOG_LEVEL": "ERROR"
}
},
"awslabs.cost-analysis-mcp-server": {
"command": "uvx",
"args": ["awslabs.cost-analysis-mcp-server@latest"],
"env": {
"AWS_PROFILE": "your-aws-profile",
"FASTMCP_LOG_LEVEL": "ERROR"
}
},
"awslabs.cdk-mcp-server": {
"command": "uvx",
"args": ["awslabs.cdk-mcp-server@latest"],
"env": {
"FASTMCP_LOG_LEVEL": "ERROR"
}
},
"awslabs.aws-documentation-mcp-server": {
"command": "uvx",
"args": ["awslabs.aws-documentation-mcp-server@latest"],
"env": {
"FASTMCP_LOG_LEVEL": "ERROR"
},
"disabled": false,
"autoApprove": []
}
}
}
See individual server READMEs for specific requirements and configuration options.
Comprehensive documentation for all servers is available on our documentation website.
Documentation for each server:
Documentation includes:
See CONTRIBUTING for more information.
This project is licensed under the Apache-2.0 License.
Before using an MCP Server, you should consider conducting your own independent assessment to ensure that your use would comply with your own specific security and quality control practices and standards, as well as the laws, rules, and regulations that govern you and your content.