Model Context Protocol

Enterprises are now deploying AI assistants and autonomous agents into real workflows, where they must query systems, request access, and take action on behalf of users. Without a standard interface, every integration becomes a custom project with its own security gaps, and every agent becomes an ungoverned actor in your environment. To bring these agents under consistent control, enterprises need a common way for AI to interact with governed systems.

What is Model Context Protocol (MCP)?

The Model Context Protocol (MCP) defines that common interface. MCP is an open standard that defines a common way for AI agents to connect to enterprise systems. Instead of custom plug-ins and point integrations, AI works through a single, structured interface that is easier to secure and govern. For identity governance, MCP creates the foundation for two related capabilities: AI that supports IGA, and IGA that governs AI.

A standardized, secure interface between AI and identity

Enterprises rely on many operational systems, each with different APIs and data models. MCP defines a single communication standard for AI agents, so you integrate once with an enterprise MCP layer instead of building custom links to every system. Through that layer, the agent can create tickets, request access, or look up user information via one consistent interface, while MCP manages translation, routing, and security in the background.

A governed pathway for AI queries and actions

MCP defines how AI agents reach your enterprise systems. Identity governance defines what they are allowed to do when they get there. MCP carries structured requests into your environment, and Omada Identity Cloud evaluates them through its policy engine, SoD controls, risk models, and business workflows. MCP handles connectivity; Omada acts as the control plane that decides which AI-initiated actions are safe and aligned with policy.

When an AI agent submits a request to look up a user, grant access, or remove a role, it flows through the enterprise MCP layer under a governed identity managed in Omada. That identity carries only required permissions and can be fully lifecycle-managed. Omada interprets each request in a business context, checking policies, risk scores, and approval chains before any change is made in downstream enterprise systems.

MCP and Omada both record their part of the transaction. MCP logs which agent invoked which tool. Omada records the governance decision and exact changes to identities and entitlements. Correlating these views gives security and audit teams a single place to trace AI-driven activity from query to system change.

Identity as the control plane for AI

The same foundation enables IGA for AI. Omada treats AI agents as identities with owners, roles, and lifecycle states so they can be governed alongside humans. Policies define which MCP tools an agent is allowed to use, on whose behalf, and under what conditions. As activity flows through MCP, it becomes a rich signal for analytics and future controls that help organizations detect agents that call unexpected tools, operate outside acceptable risk thresholds, or accumulate excessive access.

This establishes the basis for a continuous governance loop. AI agents can rely on Omada, via MCP, when they need to access or act on identity data. In turn, that activity becomes input to how Omada observes and shapes agent behavior over time. Identity governance is evolving into the control plane for both human and AI-driven activity, helping ensure agentic operations stay within clear, auditable policy boundaries.

Get started using Omada’s MCP server

The Omada MCP Server provides a standardized, secure way to connect with AI assistants, automation tools, and other enterprise systems. To receive access to the Omada Identity MCP Server GitHub project, contact your Omada customer representative or the Omada Support Desk.