As organizations adopt AI agents, large language models (LLMs), and Model Context Protocol (MCP) gateways, securing access to enterprise data, tools, and services becomes increasingly complex. AI agents can act on behalf of users, interact with multiple systems, and execute actions autonomously, introducing new authorization challenges.
While authentication verifies the identity of a user or AI agent, it doesn't determine what actions that agent should be allowed to perform. Organizations need fine-grained, policy-driven authorization to evaluate access requests based on identity, permissions, resource sensitivity, and context.
In this on-demand webinar, Axiomatics experts explore how centralized authorization policies can help secure AI agents, MCP gateways, and retrieval-augmented generation (RAG) pipelines while maintaining control over access to enterprise resources.
How to Secure AI Agents and MCP Gateways
AI agents and MCP gateways introduce new access control challenges as autonomous systems interact with enterprise data, applications, and tools.
In this webinar, our experts explore:
- Why authentication isn't enough: Understand why verifying an AI agent's identity doesn't guarantee it should have access to every tool, action, or resource.
- Fine-grained authorization for AI agents: Learn how policy-driven authorization controls what agents can access and which actions they can perform.
- Securing MCP gateways and AI workflows: Explore how centralized policies can enforce access requirements across MCP interactions, LLM applications, and RAG pipelines.
- Policy-driven authorization in action: See a demonstration of how Axiomatics helps secure AI interactions with centralized authorization policies.
