The Model Context Protocol (MCP) is rapidly transforming how LLMs interact with enterprise data. As organizations race to build AI-native applications, MCP has emerged as the critical bridge between sophisticated language models and the complex systems that power modern business operations.
At Karini AI, we've been closely monitoring this evolution. Today, we're excited to announce a major release that makes enterprise AI integration dramatically simpler: our MCP Server for SAP.
The SAP Integration Challenge
SAP systems, including SAP HANA, SAP ECC, and SAP Business One form the operational backbone of countless Fortune 500 companies. These ERPs manage mission-critical processes across manufacturing, finance, and supply chain operations. Yet despite their ubiquity, SAP systems remain difficult to integrate with modern AI applications.
The problem isn't a lack of APIs. SAP offers well-documented ODATA and ODBC interfaces. The challenge is complexity. Understanding which specific objects, transactions, and schemas to invoke requires deep SAP expertise that's difficult to embed directly into agentic AI workflows.
A Smarter Approach
Here's where things get interesting: state-of-the-art LLMs have already been trained on SAP data schemas. They possess surprisingly robust knowledge of common standards, transactions, and API specifications. The missing piece has been a bridge that lets these models leverage that knowledge effectively.
Our SAP MCP Server provides exactly that bridge through four powerful, purpose-built tools:
Discovery and Schema Understanding
- list_saphana_tables - AI agents can explore your SAP environment by listing available tables across schemas, understanding the data landscape before taking action
- get_saphana_table_schema - Agents retrieve detailed column definitions, data types, and constraints, enabling them to construct semantically correct queries
Data Operations and Analysis
- execute_saphana_query - Full SQL query capabilities (SELECT, INSERT, UPDATE, DELETE) with proper schema.table syntax handling, letting agents read and modify SAP data directly
- count_saphana_table_records - Quick record counting with optional filtering, perfect for validation checks and data quality assessments
What makes this powerful is the combination: agents can discover what data exists, understand its structure, validate assumptions through counts, and execute operations, all through a unified protocol. They don't need hard-coded knowledge of your specific SAP implementation. They can explore, learn, and act.
What You Can Build
The implications are immediate and practical. With our MCP server, you can now automate complex exception handling and validation scenarios across core business processes:
- Procure-to-Pay workflows that intelligently handle invoice mismatches and approval routing
- Order-to-Cash processes that automatically validate pricing, inventory, and credit terms
- Order processing automation that manages exceptions and updates across multiple systems
- Invoice processing that reconciles discrepancies and flags anomalies
These aren't simple chatbots. They're agentic workflows that can reason about your SAP data, understand business context, and take appropriate actions all while maintaining the security and governance standards your enterprise demands.
Getting Started
We're working with select partners to deploy these capabilities in production environments. If you're interested in exploring how SAP MCP integration could transform your operations, we'd love to hear from you.
The future of enterprise AI isn't about replacing your existing systems, it's about making them dramatically more intelligent and responsive. With MCP, that future is arriving faster than many expected.