How CData’s MCP Supports Scalable AI Across SAP Environments

Enterprises are actively embedding AI into SAP environments. Copilots, agents, and assistants now support finance, HR, supply chain, and customer workflows. Early deployments often show promise. However, AI faces challenges when reasoning continuously across distributed SAP and non-SAP systems.

Now, data often spans SAP ECC, SAP S/4HANA, and SAP HANA-based analytics, as well as numerous cloud applications. Traditional integration patterns—replication, rigid APIs, and custom services—were built for reporting and batch analytics, not for AI systems that require live, contextual, multi-source access without replication. This creates a structural gap between what data architecture delivers and what AI systems need.

Organizations bridging this gap rethink connectivity as shared infrastructure rather than bespoke plumbing. Emerging standards such as the Model Context Protocol (MCP) enable this shift, and platforms like CData Connect AI operationalize it, giving SAP environments the governed, real-time access that production AI demands for enterprise-grade execution.

MCPs: The Connective Tissue for Enterprise AI

Despite the growing presence of AI in enterprise workflows, MCPs remain a relatively new technology. Many organizations have yet to adopt them, often because early AI pilots succeed with bespoke integrations or ad-hoc connectors.

The value of MCP appears when AI moves beyond isolated use cases—agents must scale across SAP and non-SAP systems, respect governance policies, and reason in real time.

Data Connect AI provides an MCP for SAP systems, including SAP S/4HANA, and cloud applications, such as SAP SuccessFactors, SAP Concur, and SAP Ariba. The platform delivers plug-and-play connectors that transform disparate APIs into standardized, machine-readable interfaces. Identity-first security enforces source-system permissions, while real-time monitoring, structured logging, and robust error handling ensure reliable execution at scale. Cross-platform compatibility lets agents access live SAP data across environments while IT retains full observability, security, and compliance control.

The platform enables AI-driven automation, letting agents query, orchestrate, and act across SAP and non-SAP systems, accessing live data directly from source systems without replication or intermediary layers. Its scalable architecture supports growth in agents, users, and data sources, while automated deployment, validation, and lifecycle management reduce operational overhead and simplify production-scale adoption.

Together, these capabilities turn MCP from an emerging standard into deployable infrastructure, enabling governed, enterprise-grade AI inside SAP landscapes. Organizations can scale AI confidently, accelerating adoption and operational impact.

Preserving SAP Semantics While Integrating AI Agents

CData Connect AI delivers direct, production-ready access across SAP systems supporting enterprise operations, spanning core and cloud workloads.

Unlike generic database drivers or one-size-fits-all tools, Connect AI preserves SAP-specific structures and rules, modeling core business objects, relationships, and data semantics. This enables AI agents to interact with transactional and analytical data accurately and contextually at scale.

Starting with SAP’s core data foundation— SAP ECC, SAP S/4HANA, and SAP HANA analytics—CData Connect AI provides native, governed access to transactional and analytical data. AI agents then leverage this structured access to reason over financial, supply chain, and operational information in place, preserving context and performance.

In the cloud, Connect AI supports the applications SAP teams use most—SAP SuccessFactors, SAP Concur, and SAP Ariba—providing real-time, native connectivity. AI agents access high-volume operational data while maintaining application-specific structures and business logic, keeping HR, T&E, and procurement workflows accurate.

Agents can query SuccessFactors for workforce planning, Concur for expense analysis, and Ariba for purchase orders and supplier interactions. Governed access, source-system permissions, and standardized interfaces let AI scale across cloud workloads without custom connectors or replication.

Connect AI also provides native connectivity for SAP Business One, supporting thousands of mid-market companies and select larger organizations. Across SAP systems, Connect AI provides structured, governed access that preserves SAP semantics, ensuring agents operate reliably and enterprise-wide AI adoption is seamless.

Extending Connectivity Across 350+ Enterprise Systems

CData Connect AI applies the same governance and operational clarity to over 350 enterprise systems, including NetSuite, Salesforce, Snowflake, and ServiceNow. This broad connectivity allows organizations to scale AI initiatives across platforms, correlating transactional, analytical, and cloud data in real time.

For example, CData Connect AI provides foundational infrastructure for Microsoft-based AI agents, enabling Copilot Studio and Agent 365 to interact with hundreds of enterprise systems via a single MCP layer. It handles schema translation, protocol differences, pagination, and query optimization, while exposing metadata, entity relationships, and business logic from source systems—giving agents structured, context-rich data.

An identity-first security model enforces RBAC, OAuth, and SSO policies, limits AI actions, and ensures full auditability, allowing enterprise-scale deployments with governance and reliability. Sabin Nair, group product manager at Microsoft, said, “By integrating with CData’s Connect AI, we empower customers to build agents in Copilot Studio that seamlessly connect to hundreds of enterprise data sources.”

As with Microsoft integrations, CData Connect AI enables agents built with Databricks’ tooling to treat external enterprise systems as first-class inputs without custom connectors. Named a Featured Launch Partner for the MCP in Databricks Marketplace, Connect AI decouples agent logic from data access, letting teams evolve models, pipelines, and workflows without reworking integrations. Agents operate on live enterprise data at scale, reducing latency, avoiding redundant pipelines, and maintaining governance.

This approach lets organizations build and deploy AI agents efficiently, ensuring secure, reliable access to live enterprise data, enabling multi-system scaling, and delivering actionable insights across workflows. Ariel Amster, director of technology partner management at Databricks, said, “This capability significantly accelerates [Agent Bricks users’] ability to build context-aware AI apps and agents that deliver real business impact.”

MCPs Provide Infrastructure for Growth

Across industries, organizations are using MCPs to connect AI systems with operational data, coordinate actions across applications, and reduce reliance on manual integration work. CData Connect AI supports these deployments through governed, real-time access to enterprise data, helping early adopters move beyond pilots.

As Upstream USA, a nonprofit healthcare organization, expanded, leadership teams required visualizations of growing data volumes. The organization adopted Power BI to improve reporting, but it lacked native connectivity with Sage Intacct. Its data architecture did not have the connectivity layer needed to support boardroom decision-making.

Upstream sought automated access to financial data and choose CData Connect AI to link Sage Intacct with Power BI. Within days, managers were accessing reports daily, analyzing data for their regions, while the data team saved over seven hours per week.

John Hatch, senior data, analytics, and technology analyst at Upstream, said, “having a working proof of concept on the first day was by far the defining decision point for us.”

The improved visibility allowed leadership to make informed budget allocations and predict financial trends more accurately. John Hatch, senior data, analytics, and technology analyst at Upstream, said, “regional directors can now see what percentage of the numerous health agencies we work with in the Midwest are on budget – and they can see that in a matter of moments, whereas before that we just could not answer that question.”

Connect AI relieved pressure on the data team and ensured leadership had timely insights to guide growth and resource allocation.

After Scorpion, a software company, grew from a few hundred to over a thousand employees, it adopted the CData Google Sheets Power BI Connector to streamline reporting and reduce manual CSV work. Later, as leadership required deeper transactional-level insights, the team sought a solution to unify Sage Intacct and Vena data, enabling real-time, integrated analysis of vendor activity, budgets, and performance metrics.

Scorpion implemented Connect AI, enabling connectivity to data sources directly in Power BI, and expanded it to surface sensitive payroll data from ADP, allowing HR to analyze salary ranges and make informed budget decisions. CData’s access controls ensured sensitive information remained secure while supporting cloud-based reporting.

It transformed Scorpion’s approach to data management. “I’m not limited to using it in just one reporting tool or connecting to one system,” explained Nathan Thompson, VP of financial planning and analysis at Scorpion. “I know we have versatility if we experience change, which is really important to me because we’re not tied to some proprietary system of using that data in certain ways.”

These cases demonstrate how CData Connect AI links disparate data systems, reducing operational complexity and overhead.

More importantly, they show how growing organizations establish the infrastructure needed to manage new variables, scale headcount, and integrate diverse information sources—enabling growth without being slowed by incompatible platforms or fragmented workflows.

What This Means for SAP Insiders

• MCPs bridge data silos for real-time AI. They provide a standardized connectivity layer across SAP and non-SAP systems, enabling consistent, governed, and scalable AI workflows. Companies can deploy AI enterprise-wide without ad-hoc integrations, accelerating insights and reducing operational risk.
• Connect AI preserves SAP context while enabling integration. It delivers governed, real-time access to transactional and analytical data across core and cloud SAP workloads. Business leaders gain reliable, accurate decision-making capabilities without replicating data or compromising SAP business logic.
• Connect AI transforms operational reporting into strategic infrastructure. Organizations replace manual workflows with automated, live connections, integrating multiple systems and scaling with growth. Teams reduce overhead, accelerate insights, and support expansion while maintaining governance and data reliability.