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Model Context Protocol (MCP)

Steps

  1. Overview
  2. Pre-requisites
  3. Key Choices and Guidelines
  4. Implementation

    1 Overview​

    Description​

    This page is a companion to the Pro-Code AI Agents best practice page. It provides a comprehensive reference for the Model Context Protocol (MCP), covering its architecture, SAP integration options, and implementation guidance for developers building agentic AI systems that connect to enterprise tools and data sources. For security considerations applicable to all agentic AI deployments, see the dedicated Agentic AI Security and Governance best practice page.

    The Model Context Protocol (MCP) is an open standard that enables AI agents to connect with tools, external resources, and data sources through a single, standardized interface. Rather than building unique integrations for each service, each with its own authentication methods, data formats, and API patterns, MCP provides a universal protocol through which agents can discover, invoke, and orchestrate any compliant tool.

    The core problem MCP solves is the M-times-N integration challenge: without a standard, connecting M agents to N tools requires M × N custom integrations. MCP reduces this to M + N by introducing a shared protocol layer. In practice, this means a developer builds one MCP server for their tool, and any MCP-compliant agent can use it immediately.

    For SAP, MCP is particularly relevant because enterprise AI agents need to interact with a wide range of backend systems: SAP S/4HANA, Concur, Ariba, SuccessFactors, HANA databases, and third-party services. MCP provides the protocol layer that makes these integrations standardized, maintainable, and secure, enabling the transition from isolated LLM calls to fully functional enterprise agents.

    Expected Outcome​

    After following this best practice, developers will be able to understand MCP's architecture and interaction flow, evaluate the available SAP deployment models (including the MCP Hub and custom SDK-based servers), implement MCP servers using the official SDKs, test them with the MCP Inspector, integrate with Joule via Joule Studio, and connect AI agents to SAP enterprise systems through standardized MCP interfaces.