AWS MCP Servers

A suite of specialized MCP servers that bring AWS best practices directly to your development workflow.

Available Servers

This monorepo contains the following MCP servers:

Core MCP Server

A server for managing and coordinating other AWS Labs MCP servers.

• Automatic MCP Server Management
• Planning and guidance to orchestrate AWS Labs MCP Servers
• UVX Installation Support
• Centralized Configuration

Learn more | Documentation

AWS Documentation MCP Server

A server for accessing AWS documentation and best practices.

• Search Documentation using the official AWS search API
• Get content recommendations for AWS documentation pages
• Convert documentation to markdown format

Learn more | Documentation

Amazon Bedrock Knowledge Bases Retrieval MCP Server

A server for accessing Amazon Bedrock Knowledge Bases.

• Discover knowledge bases and their data sources
• Query knowledge bases with natural language
• Filter results by data source
• Rerank results

Learn more | Documentation

AWS CDK MCP Server

A server for AWS CDK best practices.

• AWS CDK project analysis and assistance
• CDK construct recommendations
• Infrastructure as Code best practices

Learn more | Documentation

Cost Analysis MCP Server

A server for AWS Cost Analysis.

• Analyze and visualize AWS costs
• Query cost data with natural language
• Generate cost reports and insights

Learn more | Documentation

Amazon Nova Canvas MCP Server

A server for generating images using Amazon Nova Canvas.

• Text-based image generation with customizable parameters
• Color-guided image generation with specific palettes
• Workspace integration for saving generated images
• AWS authentication through profiles

Learn more | Documentation

What is the Model Context Protocol (MCP) and how does it work with AWS MCP Servers?

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.

— Model Context Protocol README

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.

Installation and Setup

Each server has specific installation instructions. Generally, you can:

1. Install uv from Astral
2. Install Python using uv python install 3.10
3. Configure AWS credentials with access to required services
4. Add the server to your MCP client configuration

Example 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.core-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.

Documentation

Comprehensive documentation for all servers is available on our documentation website.

Documentation for each server:

• Core MCP Server
• Amazon Bedrock Knowledge Bases Retrieval MCP Server
• AWS CDK MCP Server
• Cost Analysis MCP Server
• Amazon Nova Canvas MCP Server

Documentation includes:

• Detailed guides for each server
• Installation and configuration instructions
• API references
• Usage examples

Security

See CONTRIBUTING for more information.

License

This project is licensed under the Apache-2.0 License.

Disclaimer

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.