AI Core MCP Server

An MCP (Model Context Protocol) server for SAP AI Core, powered by odata-mcp-proxy. It exposes SAP AI Core APIs as MCP tools, allowing AI assistants like Claude to manage your AI Core landscape through natural language.

The entire server is defined through a single JSON config file -- no custom code required.

How It Works

This project uses the odata-mcp-proxy npm package, which maps OData/REST services to MCP tools based on a configuration file. You provide a config describing your APIs and entity sets, and the proxy generates the corresponding MCP tools automatically.

AI Assistant (Claude, Cursor, etc.)
        |
        | MCP Protocol (HTTP or stdio)
        v
  odata-mcp-proxy
        |
        | REST + OAuth2 (via BTP Destination Service)
        v
  SAP AI Core APIs

Think of it like the SAP Application Router -- a ready-made runtime you configure, not code you write.

Related MCP server: SAP OData to MCP Server

Exposed AI Core APIs

The config file (ai-core-api-config.json) defines two API groups:

Lifecycle Management (/v2/lm)

Administration (/v2/admin)

Prerequisites

• Node.js 18+ (20+ recommended)

• SAP BTP account with SAP AI Core provisioned

• BTP Destination configured for the AI Core API (AI_CORE) with OAuth2 authentication

• Cloud Foundry CLI (cf) and MBT Build Tool (mbt) for deployment

Project Structure

ai-core-mcp-server/
├── package.json                # Start script + odata-mcp-proxy dependency
├── ai-core-api-config.json     # API configuration (defines all MCP tools)
├── mta.yaml                    # BTP Cloud Foundry deployment descriptor
├── xs-security.json            # XSUAA OAuth2 configuration
├── default-env.json            # Local dev credentials (gitignored)
└── LICENSE

Getting Started

1. Install dependencies

npm install

2. Configure BTP destination

Create a BTP Destination pointing to the AI Core API:

The destination should use OAuth2 client credentials authentication with the AI Core service key.

3. Local development

Create a default-env.json with your BTP service bindings (XSUAA, Destination, Connectivity) to run locally:

npm start

This runs odata-mcp-proxy --config ai-core-api-config.json.

4. Deploy to BTP

npm run build:btp     # Build MTA archive
npm run deploy:btp    # Deploy to Cloud Foundry

The MTA deployment provisions three service instances:

• Destination (lite) -- resolves API endpoints and manages OAuth2 tokens

• Connectivity (lite) -- enables secure backend connectivity

• XSUAA (application) -- handles OAuth2 authentication with role-based access control

Security

The XSUAA configuration (xs-security.json) defines three role templates:

OAuth2 redirect URIs are pre-configured for Claude.ai, Cursor, Microsoft Teams, and local development.

Creating Your Own MCP Server

This project demonstrates how easy it is to create a custom MCP server using odata-mcp-proxy. To build your own:

1. Create a new project and install the dependency:

   mkdir my-mcp-server && cd my-mcp-server
   npm init -y
   npm install odata-mcp-proxy

2. Add a start script to package.json:

   {
     "scripts": {
       "start": "odata-mcp-proxy --config my-api-config.json"
     }
   }

3. Define your APIs in a config file (my-api-config.json):

   {
     "server": {
       "name": "my-mcp-server",
       "version": "1.0.0",
       "description": "My custom MCP server"
     },
     "apis": [
       {
         "name": "my-api",
         "destination": "MY_BTP_DESTINATION",
         "pathPrefix": "/api/v1",
         "csrfProtected": true,
         "entitySets": [
           {
             "entitySet": "Products",
             "description": "Product catalog",
             "category": "master-data",
             "keys": [{ "name": "Id", "type": "string" }],
             "operations": { "list": true, "get": true, "create": false, "update": false, "delete": false }
           }
         ]
       }
     ]
   }

4. Add your mta.yaml, xs-security.json, and BTP Destinations, then deploy. That's it -- no code to write.

License

MIT