SAP CPI MCP Server

A Python-based MCP server and optional AI agent for connecting to SAP Cloud Integration / SAP CPI.

This project exposes SAP CPI APIs as MCP tools so an MCP-compatible client or AI agent can inspect CPI metadata, runtime artifacts, integration packages, message processing logs, and failed messages.

Table of Contents

• Overview
• Architecture
• Features
• Project Structure
• Prerequisites
• Setup
• Environment Variables
• Run the MCP Server
• Test with MCP Inspector
• Available MCP Tools
• Run the AI Agent
• Common Commands
• Troubleshooting
• Security Notes
• GitHub Setup
• License

Overview

The server connects to SAP CPI using OAuth client credentials and exposes CPI operations through the Model Context Protocol, or MCP.

An AI client can connect to this MCP server and use the available tools to answer questions such as:

• What are the latest CPI message processing logs?
• Are there any failed messages?
• Which runtime artifacts are deployed?
• What integration packages are available?
• What OData entities are exposed by this CPI tenant?

Architecture

User / AI Client / MCP Inspector
        |
        | MCP over Streamable HTTP
        v
Python MCP Server
        |
        | HTTPS + OAuth client credentials
        v
SAP Cloud Integration / SAP CPI APIs

Optional AI agent flow:

User Question
        |
        v
agent.py
        |
        | LLM tool-calling
        v
MCP Server
        |
        v
SAP CPI APIs

Features

• Python MCP server using FastMCP
• Streamable HTTP MCP transport
• SAP CPI OAuth client credentials authentication
• JSON response handling using HTTP Accept: application/json
• CPI OData metadata inspection
• CPI message processing log listing
• Failed message search
• Runtime artifact listing
• Integration package listing
• Optional AI agent using OpenRouter
• MCP Inspector support for local testing

Project Structure

cpi-mcp-server/
├── server.py
├── agent.py
├── requirements.txt
├── .env.example
├── .gitignore
└── README.md

Prerequisites

Install these before running the project:

• Python 3.11 or later
• Node.js LTS, only required for MCP Inspector
• Git
• SAP Integration Suite / SAP CPI tenant
• SAP BTP service key or OAuth client with CPI API access
• Optional OpenRouter API key for the AI agent

Setup

Clone the repository:

git clone https://github.com/jacksnh/CPI-MCP-SERVER.git
cd CPI-MCP-SERVER

Create a Python virtual environment:

python -m venv .venv

Activate the virtual environment on Windows PowerShell:

.\.venv\Scripts\Activate.ps1

If PowerShell blocks activation, run:

Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser

Then activate again:

.\.venv\Scripts\Activate.ps1

Install dependencies:

python -m pip install -r requirements.txt

If requirements.txt is not available yet, install manually:

python -m pip install "mcp[cli]" httpx python-dotenv

Environment Variables

Create a .env file in the project root.

You can copy .env.example:

copy .env.example .env

Then edit .env:

notepad .\.env

Example .env:

CPI_BASE_URL=https://your-cpi-host
CPI_TOKEN_URL=https://your-token-host/oauth/token
CPI_CLIENT_ID=your-client-id
CPI_CLIENT_SECRET=your-client-secret

OPENROUTER_API_KEY=your-openrouter-api-key
OPENROUTER_MODEL=openai/gpt-4o-mini
MCP_SERVER_URL=http://127.0.0.1:8000/mcp

Important: do not commit .env to GitHub.

Run the MCP Server

Start the server:

python server.py

Expected output:

Starting SAP CPI MCP Server on http://127.0.0.1:8000/mcp
Uvicorn running on http://127.0.0.1:8000

Keep this terminal open while using MCP Inspector or the AI agent.

The MCP server URL is:

http://127.0.0.1:8000/mcp

Test with MCP Inspector

Install Node.js LTS if npx is not available.

Start MCP Inspector in a second terminal:

npx -y @modelcontextprotocol/inspector

Open the URL printed by Inspector in the terminal. It usually looks like:

http://localhost:6274/?MCP_PROXY_AUTH_TOKEN=...

Use these settings in MCP Inspector:

Transport Type: Streamable HTTP
URL: http://127.0.0.1:8000/mcp
Connection Type: Via Proxy

Click Connect.

Start by running the health_check tool.

Available MCP Tools

The server can expose tools such as:

Tool	Purpose
health_check	Checks whether the MCP server is running.
get_cpi_metadata	Retrieves CPI OData service metadata.
list_message_processing_logs	Lists recent CPI message processing logs.
search_failed_messages	Searches recent failed CPI messages.
get_message_processing_log	Gets one message processing log by message GUID.
list_integration_runtime_artifacts	Lists deployed CPI runtime artifacts.
get_integration_runtime_artifact	Gets one runtime artifact by ID.
list_integration_packages	Lists CPI integration packages.

Example tool input for logs:

{
  "top": 5
}

Run the AI Agent

Make sure the MCP server is already running in one terminal:

python server.py

Open a second terminal and run:

python agent.py

Example prompts:

Run a health check.
Show me the latest 5 CPI message processing logs and summarize them.
Find the latest 5 failed CPI messages and explain likely root causes.
List deployed CPI runtime artifacts.

The agent connects to the MCP server, discovers available tools, calls the relevant tool, and summarizes the result.

Common Commands

Activate virtual environment:

.\.venv\Scripts\Activate.ps1

Run MCP server:

python server.py

Run AI agent:

python agent.py

Run MCP Inspector:

npx -y @modelcontextprotocol/inspector

Check if port 8000 is listening:

netstat -ano | findstr :8000

Check installed Python packages:

python -m pip list

Troubleshooting

ECONNREFUSED 127.0.0.1:8000

The MCP server is not running.

Start it in a separate terminal:

python server.py

Wait for:

Uvicorn running on http://127.0.0.1:8000

npx is not recognized

Node.js is not installed or is not on the Windows PATH.

Install Node.js LTS, then reopen VS Code or PowerShell and verify:

node -v
npm -v
npx -v

Not Acceptable: Client must accept text/event-stream

This is normal if you test /mcp with Invoke-WebRequest or a browser directly.

The /mcp endpoint expects an MCP client, such as MCP Inspector.

KeyError: CPI_BASE_URL

The .env file is missing, not saved, or not being loaded.

Check that .env is in the same folder as server.py and contains:

CPI_BASE_URL=https://your-cpi-host

501 Not Implemented

The CPI tenant may not support the endpoint being called, or the endpoint may differ for your tenant type.

Run:

get_cpi_metadata

Then check which OData entity sets are available.

401 Unauthorized

Possible causes:

• Wrong CPI_CLIENT_ID
• Wrong CPI_CLIENT_SECRET
• Wrong CPI_TOKEN_URL
• OAuth client does not belong to the CPI tenant

403 Forbidden

The OAuth client exists but does not have the required CPI API roles.

Check SAP BTP role collections and service key permissions.

404 Not Found

Possible causes:

• Wrong CPI_BASE_URL
• Wrong CPI region or tenant host
• Endpoint is unavailable in your tenant

Security Notes

Never commit secrets to GitHub.

Do not commit:

.env
.venv/

Recommended .gitignore:

.env
.venv/
__pycache__/
*.pyc
node_modules/
.vscode/
.DS_Store

If credentials were ever shown in screenshots, logs, chat messages, or committed to GitHub, rotate them immediately.

For production use:

• Use a secret manager instead of .env
• Use least-privilege SAP BTP service credentials
• Keep read-only and write-enabled credentials separate
• Add authentication in front of the MCP server
• Avoid exposing the MCP server publicly without access control
• Add audit logging for tool calls

GitHub Setup

Initialize Git:

git init

Add remote:

git remote add origin https://github.com/jacksnh/CPI-MCP-SERVER.git

If remote already exists:

git remote set-url origin https://github.com/jacksnh/CPI-MCP-SERVER.git

Add files:

git add .

Commit:

git commit -m "Add SAP CPI MCP server and AI agent"

Push:

git branch -M main
git push -u origin main

License

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