Sap Analytics Cloud

SAP Analytics Cloud MCP Server

An MCP (Model Context Protocol) server that exposes the SAP Analytics Cloud REST API as 90 tools consumable by any MCP-compatible client (Custom Agent, Claude Desktop, Claude Code, Cursor, etc.).

What it does

The server authenticates against an SAC tenant using OAuth 2.0 Client Credentials and manages CSRF tokens and session cookies automatically. It then exposes the full SAC REST API surface as discrete MCP tools grouped into 11 service areas:

Plus a ping connectivity check tool (90 total), and Prompt support for guided workflows.

Prerequisites

• Node.js >= 18.0 (required for native fetch and Headers.getSetCookie)
• npm
• An SAP Analytics Cloud tenant with an OAuth client (see below).

SAC Tenant Setup

1. Open your SAC tenant and go to System > Administration > App Integration > Add a New OAuth Client.
2. Set the purpose to Interactive Usage and API Access.
3. Note down the following four values:
   • Base URL -- https://<tenant>.<datacenter>.sapanalytics.cloud
   • Token URL -- shown on the OAuth client detail page
   • Client ID
   • Client Secret

Installation & Build

git clone https://github.com/JumenEngels/sap_analytics_cloud_mcp
cd sap_analytics_cloud_mcp
npm install
npm run build

Quick Start: Agent Client

The easiest way to test the server locally (after doing mcp setup above) is using the included Agent Client. It connects to the server and uses an LLM (SAP AI Core, Anthropic, OpenAI, etc.) to interact with your SAC tenant.

1. Setup Configuration

Navigate to the client directory and run the setup script:

cd AgentClient
npm install
npm run setup

This creates mcp_agentclient.json. Open this file and fill in your credentials:

1. SAC Credentials: Fill in sac section with the values from "SAC Tenant Setup".
2. LLM Credentials: Fill in aicore, anthropic, or openai sections.
3. Default Provider: Set "defaultProvider" to your preferred LLM (e.g., "genaicore", "anthropic").

2. Run the Client

npm run build
npm start

The client will automatically load all necessary configuration (both for the LLM and the SAC Server) from your JSON file.

Configuration (For standard MCP Clients)

If you are using Claude Desktop, Cursor, or another MCP client, you need to configure the server environment variables directly.

The server reads four required environment variables at runtime:

MCP Client Configuration

Claude Desktop

To automatically generate a configuration file with the correct absolute path:

npm run setup

This creates an mcp_config.json file in the project root. fill in your SAC credentials there and copy the content to your Claude Desktop config file.

Cursor / Other Clients

Add the server with the command node build/index.js and set the 4 environment variables in the client's configuration UI.

Smart Query

The smart_query tool simplifies data access by intelligently routing your request:

• Relational: Simple SELECT * queries are routed to the OData API for raw entity data.
• Analytical: Queries with aggregations (SUM, COUNT, GROUP BY) are analyzed and routed to the Widget Query API.

SELECT SUM(Amount) FROM Model123 GROUP BY Region

Prompts

The server provides pre-defined prompts to guide users through common workflows:

1. explore_content: Discover stories and files in your tenant.
2. analyze_story: Deep dive into a specific story's metadata and dependencies.
3. system_health_check: Quick status check of connectivity and recent failures.

Deployment

Docker

docker build -t sac-mcp-server .
docker run -e SAC_BASE_URL="..." ... sac-mcp-server

Development

Watch mode recompiles on every file change:

npm run dev

Security Notes

• Write Operations: All tools that modify data require allowalteration=true argument.