Serverless Web MCP Server
This project implements a server based on the Model Context Protocol (MCP) for deploying web applications to AWS serverless infrastructure, supporting automatic deployment of front - end, back - end, and full - stack applications.
rating : 2.5 points
downloads : 17
What is the Serverless Web MCP Server?
This is a server that follows the Model Context Protocol (MCP) specification, specifically designed to provide AI coding agents with the ability to deploy web applications to AWS serverless infrastructure. It simplifies the deployment process, allowing AI to manage AWS resources like human developers.How to use the Serverless Web MCP Server?
You can connect to this server through AI clients that support MCP, such as Claude, and then use the provided tool commands to deploy and manage web applications. The server will handle all the configuration and deployment details of the AWS infrastructure.Use cases
Suitable for AI agents that need to quickly deploy web applications to AWS, especially in scenarios where automatic deployment of backend APIs, frontend websites, or full - stack applications is required.Main features
Unified deployment serviceSupports three deployment types: pure backend, pure frontend, and full - stack applications. Uses a unified interface to simplify the deployment process.
Lambda Web AdapterComes with an AWS Lambda Web Adapter, allowing common web frameworks to run without code modification.
Resource discoveryProvides query functions for deployment templates and existing deployment status to help AI understand available resources.
Monitoring toolsComes with built - in log and metric query functions, making it easy for AI to monitor the status of deployed applications.
Advantages and limitations
Advantages
Simplifies the AWS serverless deployment process. AI doesn't need to have in - depth knowledge of AWS details.
Supports multiple web frameworks and runtimes, with good compatibility.
Provides a unified deployment interface, reducing the learning cost.
Comes with built - in monitoring and logging functions, facilitating problem troubleshooting.
Limitations
Currently only supports the AWS platform.
Requires pre - configured AWS credentials.
Complex custom deployments may require additional configuration.
How to use
Install the server
Install the server globally via npm or build it from the source code.
Configure the AI client
Add MCP server information to the configuration file of the AI client (e.g., Claude).
Start deployment
Send deployment commands through the AI client, specifying the project type and configuration.
Usage examples
Deploy a React frontend applicationDeploy the built React application to S3 and CloudFront
Create a Node.js API serviceDeploy an Express.js backend API to Lambda and API Gateway
Full - stack application deploymentDeploy the frontend and backend simultaneously and configure the connection between them
Frequently Asked Questions
Do I need to have prior knowledge of AWS?
Which programming languages are supported?
How to view the deployment status?
What if the deployment fails?
Related resources
Model Context Protocol official website
Official documentation for the MCP protocol
AWS SAM documentation
Documentation for the AWS serverless application model
GitHub repository
Project source code
Lambda Web Adapter
Adapter for running web frameworks on Lambda
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