AWS MCP Servers

What is AWS MCP Servers?

A suite of specialized MCP servers that provide AI applications access to AWS documentation, contextual guidance, and best practices. It uses the Model Context Protocol to integrate with AI tools like IDEs and chatbots, enabling enhanced cloud-native development and infrastructure management.

How to use AWS MCP Servers?

Install and configure the desired MCP server(s) via pip (or uvx for some) and set up the MCP client configuration files such as cline_mcp_settings.json, .cursor/mcp.json, or windsurf/mcp_config.json depending on the host application. Alternatively, run the servers in containers. Examples include using Cline with Amazon Bedrock, Cursor, or Windsurf.

Key features of AWS MCP Servers

• Over 20 specialized MCP servers for various AWS services.
• Improved output quality by providing relevant AWS context to foundation models.
• Access to latest AWS documentation and best practices.
• Workflow automation for CDK, Terraform, and other AWS workflows.
• Centralized configuration and orchestration via the Core MCP Server.
• Supports multiple MCP client hosts: AI coding assistants and chatbots.

Use cases of AWS MCP Servers

• Search and retrieve AWS documentation with natural language.
• Query Amazon Bedrock Knowledge Bases for enterprise data.
• Analyze and visualize AWS costs with natural language queries.
• Generate AWS architecture diagrams from code descriptions.
• Manage AWS resources directly via CloudFormation or CDK.
• Access private AWS resources through Lambda functions.