Serverless MCP Framework
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Serverless MCP Frameworklist available resources and prompts"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Serverless MCP Framework
MCP Server implementation with AWS Serverless services.
Created resources
A set of Lambda function connected to EventBridge rules that handle start, stop and task start. Create StepFunction state machine to wait until a specific date and send events.

Related MCP server: Serverless Web MCP Server
Installation
Using the SAM CLI:
sam build
sam deploy --guidedParameters
This application need some parameters when you deploy it:
EventBusName: The event bus name to connect the integration to
Project: Project identifier
Environment: Environment identifier
ServerName: The MCP server name
ServerVersion: The MCP server version
Instructions: The MCP server instructions
DomainName: The domain name of the endpoint
AcmCertificateArn: The certificate arn for the domain name provided
AuthenticationType: Authentication type for the MCP server
AuthenticationToken: The authentication token for the MCP server
OAuthIssuerUrl: The issuer URL for OAuth authentication
OAuthAuthorizationUrl: The authorization URL for OAuth authentication
OAuthTokenUrl: The token URL for OAuth authentication
OAuthRevocationUrl: The revocation URL for OAuth authentication
OAuthRedirectUris: The redirect URIs for OAuth authentication
Outputs
ServerEndpoint: The MCP server endpoint
Development
Requirements:
NodeJS >= 22.x
Install NPM modules
npm installConfigure the .env file with MCP server specifications:
SERVER_NAME=local
SERVER_VERSION=1.0.0
INSTRUCTIONS=""Configure the .env file with AWS environment configuration:
AWS_PROFILE=<your AWS profile>
AWS_REGION=<selected AWS region>
SSM_PREFIX=
TOOLS_SSM_PREFIX=
RESOURCES_SSM_PREFIX=
PROMPTS_SSM_PREFIX=
TOOL_LAMBDA_PREFIX=Run local MCP server
npm run devThe MCP server is running on http://localhost:3000/mcp.
Tool Inspector
Run the MCP Inspector
npm run inspectorConfigure the inspector with:
Transport Type:
Streamable HTTPURL:
http://localhost:3000/mcp
Connect to the MCP server with "Connect" button.
Claude Desktop
Use mcp-remote to proxy HTTP to STDIO:
{
"mcpServers": {
"example": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://xxxxxxxxxx.execute-api.eu-west-1.amazonaws.com/dev/mcp",
"--transport",
"http-only"
]
}
}
}Deploy
Requirements:
Build project
sam buildDeploy the stack
sam deploy --profile <your AWS profile> --guidedUsage
Once the solution is installed, you can extend the MCP server with resources, prompts or tools using SSM parameters and Lambda functions.
The SSM parameters must begin with the prefix /<project name>/<environment name>/, for example /mcp/dev/tools/echo.
As an example of integration you can take inspiration from the template: template.integration.yaml.
Resources
The SSM parameters must begin with prefix /<project name>/<environment name>/resources/, for example /mcp/dev/resources/example.
The content must be in valid JSON format and have the properties:
name: Resource name
uri: Resource URI, for example "config://example"
content: Resource text content
It can be declared in a SAM template as:
ExampleResourceParameter:
Type: AWS::SSM::Parameter
Properties:
Name: !Sub "/${Project}/${Environment}/resources/example"
Type: String
Value: |
{
"name": "example",
"uri": "config://example",
"content": "Just an example resource"
}Prompts
The SSM parameters must begin with prefix /<project name>/<environment name>/prompts/, for example /mcp/dev/prompts/echo.
The content must be in valid JSON format and have the properties:
name: Prompt name
description: Prompt description
inputSchema.json: JSON schema
content: Prompt template content
The content template will be elaborate with ejs with input data interpolation.
It can be declared in a SAM template as:
EchoPromptParameter:
Type: AWS::SSM::Parameter
Properties:
Name: !Sub "/${Project}/${Environment}/prompts/echo"
Type: String
Value: |
{
"name": "echo",
"description": "Execute the example tool",
"inputSchema": {
"json": {
"type": "object",
"properties": {
"message": {
"type": "string"
}
},
"required": ["message"]
}
},
"content": "Execute the tool 'echo' with the message '<%= message %>'"
}Tools
The SSM parameters must begin with prefix /<project name>/<environment name>/tools/, for example /mcp/dev/tools/echo.
The content must be in valid JSON format and have the properties:
name: Prompt name
description: Prompt description
inputSchema.json: JSON schema
The related Lambda function that will be executed must be name as <project name>-<environment name>-tools-<tool name>, for example mcp-dev-tools-echo.
The function input and output must respect the Converse API pattern.
The parameter can be declared in a SAM template as:
EchoToolParameter:
Type: AWS::SSM::Parameter
Properties:
Name: !Sub "/${Project}/${Environment}/tools/echo"
Type: String
Value: |
{
"name": "echo",
"description": "Print the message provided in input",
"inputSchema": {
"json": {
"type": "object",
"properties": {
"message": {
"type": "string"
}
},
"required": ["message"]
}
}
}The Lambda function implementation could be:
exports.handler = async ({ toolUseId, name, input }, context) => {
return {
name,
toolUseId,
status: 'success',
content: [{
text: input.message
}]
}
}declared inline in a SAM template:
EchoToolFunction:
Type: AWS::Serverless::Function
Properties:
FunctionName: !Sub "${Project}-${Environment}-tools-echo"
Handler: index.handler
InlineCode: |
exports.handler = async ({ toolUseId, name, input }, context) => {
return {
name,
toolUseId,
status: 'success',
content: [{
text: input.message
}]
}
}Credits
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