AWS Serverless MCP Server

What is AWS Serverless MCP Server?

The AWS Serverless MCP Server is a dedicated Model Context Protocol server that exposes capabilities for serverless development on AWS. It allows AI agents or developer tools to orchestrate workflows and operations on AWS Lambda, Amazon API Gateway, Step Functions, and other serverless services. Through standardized MCP endpoints, it lets LLM-powered applications build, deploy, test, and monitor serverless applications programmatically, using best practices and the SAM CLI under the hood.

How to Configure AWS Serverless MCP Server

• Prerequisites:
  • Python 3.10+ installed
  • uv package manager (from Astral)
  • Configured AWS credentials with permissions to manage relevant AWS serverless resources
• Installation Steps:
  1. Install uv:

     pip install uv
     

  2. Install Python if not already available:

     uv python install 3.10
     

  3. Configure AWS credentials (using AWS CLI or environment variables).
  4. Update your MCP client configuration (e.g., ~/.aws/amazonq/mcp.json or other supported config files) to include:

     {
       "mcpServers": {
         "awslabs.aws-serverless-mcp-server": {
           "command": "uvx",
           "args": ["awslabs.aws-serverless-mcp-server@latest"],
           "env": {
             "AWS_PROFILE": "your-aws-profile",
             "AWS_REGION": "us-east-1",
             "FASTMCP_LOG_LEVEL": "ERROR"
           }
         }
       }
     }
     

  5. For containerized usage, build and run the Docker image (see server README for details).
  • Each MCP client (Amazon Q CLI, Cursor, Kiro, etc.) may require the configuration file in a different path. See their documentation for specifics.

How to Use AWS Serverless MCP Server

1. Start your MCP client (e.g., Amazon Q CLI, Cursor, or the app of your choice) with the AWS Serverless MCP Server enabled in the config.
2. In your chat or coding interface, prompt your LLM assistant to use the Serverless MCP Server for serverless tasks.
   • Example: "Using AWS Serverless MCP Server, create and deploy a Lambda function that responds to S3 events."
3. The assistant will leverage available tools and endpoints, possibly suggesting plans or auto-executing commands depending on your settings.
4. You may be prompted to approve actions (such as deploying, updating resources, or invoking a function).
5. Review logs, outputs, and suggested changes within your development workflow.
6. Use explicit instructions to target serverless operations, or allow the agent to automatically select the right MCP tool for your needs.

Key Features

• Lifecycle Management: Supports building, packaging, deploying, and updating serverless applications using AWS SAM CLI.
• Multi-service Orchestration: Integrate Lambda, API Gateway, Step Functions, S3 triggers, and more.
• Security and Validation: Enforces AWS security practices and can validate templates before deployment.
• Up-to-date Best Practices: Ensures code generation and deployment patterns are consistent with the latest AWS serverless recommendations.
• Workflow Automation: Allows LLMs to automate tasks like function creation, deployment, and monitoring.
• Natural Language Operations: Enables conversational agents to manage serverless infrastructure without writing CLI or CloudFormation commands directly.
• Integration with Developer Tools: Works seamlessly with Amazon Q CLI, Cursor, Cline, VSCode, Kiro, Windsurf, and other MCP-compatible environments.

Use Cases

• Automatically generate and deploy Lambda functions based on user or business requirements described in natural language.
• Scaffold, build, and deploy end-to-end serverless applications, including API Gateway endpoints, Lambda triggers, and DynamoDB integrations.
• Validate and test SAM or CloudFormation serverless templates using best practice checks.
• Update existing serverless applications with minimal manual intervention, leveraging the latest features and patterns.
• Monitor and troubleshoot deployed serverless resources by querying logs or invoking diagnostic functions.
• Educate developers interactively about serverless architectures and sample implementations directly in their IDE or chat assistant.

FAQ

Q1: Do I need to install AWS SAM CLI separately to use AWS Serverless MCP Server?
No. The AWS Serverless MCP Server wraps the functionality of the AWS SAM CLI internally; you do not need a separate SAM CLI installation unless you want to use it directly outside of MCP workflows.

Q2: Can I use AWS Serverless MCP Server for production deployments, or is it mainly for development?
While it is optimized for developer productivity and rapid prototyping, it uses the same tools and best practices as recommended for production. However, you should review outputs and follow your organization's deployment policies before pushing to production.

Q3: How does AWS Serverless MCP Server ensure security?
It respects your AWS credentials and permissions, follows AWS IAM policies, and can include security best-practices validation and role scoping to minimize risks. Always review deployment plans before approval.

Q4: What if I need to access private resources or run custom workflows?
You can configure the environment with your AWS profile or credentials, and specify resource roles or function prefixes/tags for fine-grained control over which Lambda functions or other resources are accessible.

Q5: Which environments is AWS Serverless MCP Server compatible with?
It supports all MCP-aware clients, including Amazon Q CLI, Cursor, Cline, Kiro, Windsurf, and Visual Studio Code (via compatible extensions).