sfcc-mcp-server

sfcc-mcp-server

3.4

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A Model Context Protocol (MCP) server for interacting with Salesforce Commerce Cloud (SFCC) APIs.

SFCC MCP Server

A Model Context Protocol (MCP) server for interacting with Salesforce Commerce Cloud (SFCC) APIs.

Features

  • Dynamic endpoint registration based on endpoints.json configuration
  • Automatic handling of path and query parameters
  • Support for both GET and POST requests
  • OCAPI authentication using client credentials flow
  • Support for SFCC Data API endpoints, including product search
  • Remote mode: HTTP-based server with OAuth authentication
  • Per-session configuration: Each session can use different SFCC credentials and API endpoints
  • Multi-tenant support: Multiple clients can connect to different SFCC instances simultaneously
  • Automated deployment: GitHub Actions integration for Google App Engine deployment
  • Version management: Automated versioning and deployment workflows

Installation

# Install dependencies
npm install

# Build the server
npm run build

Configuration

Create a .env file in the project root directory with the following variables:

# SFCC API Configuration
SFCC_API_BASE=https://your-instance.api.commercecloud.salesforce.com/

# Admin API Credentials (Client credentials flow)
SFCC_ADMIN_CLIENT_ID=your_admin_client_id
SFCC_ADMIN_CLIENT_SECRET=your_admin_client_secret

OCAPI Configuration

To use the SFCC Data APIs, you need to configure an API client in SFCC with the proper permissions:

API Client

  1. In SFCC Account Manager, go to API Client
  2. Create a new API client or edit an existing one
  3. Configure the OAuth settings:
    • OAuth Client ID: (your client ID)
    • OAuth Client Secret: (your client secret)
    • Default scopes: Include the scopes needed for your endpoints
    • Token Endpoint Auth Method: client_secret_post
  4. Configure API client roles:
    • Assign appropriate roles to access the required data

Business Manager

  1. In SFCC Business Manager, go to Administration > Site Development > Open Commerce API Settings
  2. See ocapi-bm-config.json for the configuration example

MCP Configuration for VSCode

  1. Open Command Palette (Ctrl/Cmd + Shift + P)
  2. Type "MCP" and choose MCP: Add Server...
  3. Choose Command (stdio) Manual Install
  4. Type node <full-path-to-your>/build/index.js for the command (replace path placeholder before submit)
  5. Name the MCP (e.g., "sfcc")
  6. Choose to configure for User or Workspace

This will create a new server definition either in your user settings.json or in workspace .vscode/mcp.json

{
    "servers": {
        "sfcc": {
            "type": "stdio",
            "command": "node",
            "args": [
                "<full-path-to-your>/build/index.js"
            ]
        }
    }
}

Now you can monitor/start/restart/stop your server through MCP: List Servers command. Work with tools by switching to Agent mode in GitHub Copilot Chat

Usage

Start the server:

node build/index.js

Endpoint Configuration

Endpoints are configured in src/endpoints.json. Each endpoint has the following structure:

{
    "path": "/your/endpoint/{param}",
    "description": "Description of what this endpoint does",
    "method": "GET",  // Optional: HTTP method (GET, POST, PUT, DELETE). Defaults to GET
    "params": [
        {
            "name": "param",
            "description": "Description of the parameter",
            "type": "string",
            "required": true
        }
    ]
}
  • path: The API endpoint path, with path parameters in curly braces
  • description: A description of what the endpoint does
  • method: HTTP method to use (GET, POST, PUT, DELETE). Defaults to GET if not specified
  • params: Array of parameter definitions
    • name: Parameter name
    • description: Parameter description
    • type: Parameter type (string, number, boolean)
    • required: Whether the parameter is required

Parameters that appear in the path (e.g., {param}) are used for path substitution. Other parameters are automatically added as query parameters.

POST Requests and Request Bodies

For POST endpoints, you can provide a JSON request body using the requestBody parameter when calling the tool. For example:

{
  "site_id": "SiteGenesis",
  "requestBody": {
    "query": {
      "text_query": {
        "search_phrase": "shirt"
      }
    },
    "sort": "price-asc",
    "count": 10
  }
}

Default Request Bodies

Endpoints can define a defaultBody property that will be used if no request body is provided. This makes it easier to use the API without needing to know the exact body structure. For example, the product_search and campaign_search endpoints have default bodies that match all items if no specific query is provided.

Path Parameters vs. Query Parameters

Parameters can be used in different ways depending on the endpoint:

  1. Path Parameters: Parameters included in the endpoint path with curly braces, like /sites/{site_id}/campaign_search
  2. Query Parameters: Other parameters appended to the URL as query strings

Example for an endpoint with path parameters (campaign_search):

{
  "site_id": "SiteGenesis",
  "requestBody": {
    "query": {
      "term_query": {
        "fields": ["enabled"],
        "operator": "is",
        "values": ["true"]
      }
    },
    "count": 20
  }
}

Tool Names

Tool names are automatically generated from endpoint paths:

  • Path separators are replaced with underscores
  • Path parameters are replaced with "by_param"
  • Names are truncated to 64 characters if needed
  • Uniqueness is ensured with numeric suffixes if needed

Example: /catalogs/{id}/products becomes catalogs_by_id_products

You can also specify a custom tool name in your endpoint configuration:

{
  "path": "/product_search",
  "toolName": "product_search",
  "description": "Search for products..."
}

Custom Handlers

You can create custom handlers for endpoints by:

  1. Specifying a custom toolName in the endpoint definition
  2. Creating a function named handler_[toolName] that will be called instead of the default handler

To create a custom handler, create a function with the name pattern handler_[toolName]. This function will be automatically detected and used instead of the default handler:

/**
 * Custom handler for product search
 * This function will be called instead of the default handler when 
 * the endpoint with toolName "product_search" is accessed
 */
export async function handler_product_search(endpoint, params) {
  console.log(`Custom handler for ${endpoint.path} called with params:`, params);
  
  // Example of custom processing before making the actual request
  if (params.requestBody && typeof params.requestBody === 'object') {
    // Modify the request if needed
    params.requestBody.custom_field = 'Added by custom handler';
  }
  
  // Call the default handler with your modified params
  const defaultHandler = getDefaultHandler();
  return await defaultHandler(endpoint, params);
}

Creating Custom Handlers

You can define custom handlers directly in your index.ts file:

/**
 * Custom handler for an endpoint with toolName "example_endpoint"
 */
async function handler_example_endpoint(endpoint, params) {
  // Your custom implementation
  // ...
}

// Make the custom handler accessible globally
(global as any).handler_example_endpoint = handler_example_endpoint;

Your custom handler function will receive two parameters:

  • endpoint: The endpoint configuration object
  • params: The parameters sent to the endpoint

The function should return the data that will be sent back to the client.

Helper Functions

Use this helper function to access the default handler:

// Helper to get the default handler
function getDefaultHandler() {
  if (typeof handleSFCCRequest === 'function') {
    return handleSFCCRequest;
  }
  if (typeof (global as any).handleSFCCRequest === 'function') {
    return (global as any).handleSFCCRequest;
  }
  throw new Error('Default handler not available');
}

Custom Handler Patterns

You can implement different patterns in your custom handlers:

Pre-processing: Modify parameters before calling the default handler

export async function handler_example(endpoint, params) {
  // Modify params
  params.customField = 'value';
  
  // Call default handler with modified params
  return await getDefaultHandler()(endpoint, params);
}

Post-processing: Enhance the result after calling the default handler

export async function handler_example(endpoint, params) {
  // Get result from default handler
  const result = await getDefaultHandler()(endpoint, params);
  
  // Modify the result
  result.enhancedField = 'value';
  
  return result;
}

Complete override: Implement custom behavior without calling the default handler

export async function handler_example(endpoint, params) {
  // Custom implementation
  return {
    custom: true,
    data: [...]
  };
}

Testing

The SFCC MCP Server includes comprehensive tests to ensure reliability and facilitate automated CI/CD processes.

Running Tests

# Run all tests
npm test

# Run tests in watch mode for development
npm run test:watch

# Run tests with coverage report
npm run test:coverage

Test Coverage

The test suite covers:

  • Tool Utilities (tests/tool-utils.test.ts): Tool name generation and schema building
  • Configuration Management (tests/config-simple.test.ts): Environment configuration and session handling
  • Integration Tests (tests/integration.test.ts): MCP server instantiation and tool registration

Test Framework

The project uses Jest with TypeScript support for testing. Tests are located in the tests/ directory and follow the naming convention *.test.ts.

Deployment

The SFCC MCP Server supports automated deployment to Google App Engine.

Quick Start

  1. Set up Google Cloud:

    npm run setup:gcp
    
  2. Deploy with versioning:

    npm run version:create
    
  3. Manual deployment:

    npm run version:deploy
    

Documentation

  • : Complete deployment setup guide
  • : Remote server configuration and usage

Available Commands

npm run setup:gcp          # Interactive Google Cloud setup
npm run version:create     # Create version and auto-deploy
npm run version:deploy     # Manual deployment with version input
npm run deploy             # Direct deployment to App Engine

License

MIT