aws-serverless-mcp

# 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.  ## Installation Using the [SAM CLI](https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/what-is-sam.html): ```bash sam build sam deploy --guided ``` ## Parameters 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](https://nodejs.org/en/download) >= 22.x Install NPM modules ```bash npm install ``` Configure 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 ```bash npm run dev ``` The MCP server is running on `http://localhost:3000/mcp`. ### Tool Inspector Run the [MCP Inspector](https://github.com/modelcontextprotocol/inspector) ```bash npm run inspector ``` Configure the inspector with: - Transport Type: `Streamable HTTP` - URL: `http://localhost:3000/mcp` Connect to the MCP server with "Connect" button. ### Claude Desktop Use [mcp-remote](https://www.npmjs.com/package/mcp-remote) to proxy HTTP to STDIO: ```json { "mcpServers": { "example": { "command": "npx", "args": [ "-y", "mcp-remote", "https://xxxxxxxxxx.execute-api.eu-west-1.amazonaws.com/dev/mcp", "--transport", "http-only" ] } } } ``` ## Deploy Requirements: - [SAM](https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/install-sam-cli.html) - [NodeJS](https://nodejs.org/en/download) >= 22.x Build project ```bash sam build ``` Deploy the stack ```bash sam deploy --profile <your AWS profile> --guided ``` ## Usage 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](./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: ```yaml 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](https://json-schema.org/) - content: Prompt template content The content template will be elaborate with [ejs](https://ejs.co/) with input data interpolation. It can be declared in a SAM template as: ```yaml 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](https://json-schema.org/) 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](https://docs.aws.amazon.com/bedrock/latest/userguide/tool-use-inference-call.html) pattern. The parameter can be declared in a SAM template as: ```yaml 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: ```js exports.handler = async ({ toolUseId, name, input }, context) => { return { name, toolUseId, status: 'success', content: [{ text: input.message }] } } ``` declared inline in a SAM template: ```yaml 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 - Repository badges by [Shields.io](https://shields.io/) - Infrastructure schema by [Cloudcraft](https://www.cloudcraft.co/)