With open standards, developers and automation administrators can enable enterprise-wide Agent Interoperability. This means that different AI Agents and automation systems can talk to each other, share data and context, and work together smoothly across different platforms and vendors. It removes automation barriers across all interfaces.

Benefits

You can connect Automation Anywhere AI Agents with agents from other companies. This allows for smooth teamwork across different platforms. It helps avoid isolated systems, keeps the system up-to-date, and ensures it can grow easily—without being tied to one vendor.

  • Seamless collaboration across Automation Anywhere AI agents, third-party AI Agents, and enterprise systems.
  • Lower integration costs by eliminating custom point-to-point connectors.
  • Dynamic discovery of tools and actions at runtime.
  • Reliable automation with built-in context continuity across calls.
  • Unified governance and security through centralized authentication, logging, and access control.
  • Composable orchestration for flexible, multi-agent workflows.

Model Context Protocol (MCP)

Model Context Protocol (MCP) is an open protocol that standardizes how AI Agents:
  • Discover tools
  • Understand capabilities
  • Execute actions across systems

Instead of building custom, point-to-point integrations, MCP provides a consistent contract for agents to request context, invoke tools, and receive structured results.

MCP defines how tools are described, how inputs and outputs are exchanged, and how execution is governed. This allows AI Agents, both Automation Anywhere AI Agents and third-party, to reliably interact with automations, APIs, and enterprise workflows without tight coupling.

For enterprises, MCP acts as a control plane for agent interactions. It enables secure access, policy enforcement, observability, and scalability as organizations move from isolated AI Assistants to coordinated, multi-agent systems. In practice, MCP turns AI Agents from passive copilots into actionable participants in real business processes.

Our MCP inbound interactions are powered by our Process Reasoning Engine (PRE). See Process Reasoning Engine and generative AI. The PRE has a deep understanding of all the Automation Anywhere automations, processes, API Tasks, and AI Agents. It knows what they are and what they can do. When a user requests to use an MCP inbound tool from a third-party AI Assistant, our PRE understands the user's intent and the context of the request. Then, it matches this with the unique automation in the Automation Anywhere repository.

With inbound connectivity, Automation Anywhere is receiving a request from third-party AI Agents and third-party AI Assistants.

Traditional APIs versus MCP Inbound

Feature Traditional APIs MCP Inbound
Tool discovery Static, predefined; require agents to know endpoints and parameters upfront Dynamic, runtime discovery; agents discover capabilities at runtime
Context Manual management Automatic continuity; maintains context continuity and governance across calls
Orchestration External, brittle; APIs break easily with unexpected inputs Built-in, composable
Vendor support Locked-in Cross-vendor, open
Security Fragmented Centralized governance

Availability

License type Accessible features
Base license
  • Ability to invoke Automation Anywhere bots, processes, API Tasks and AI Agents (if available in the customer's Control Room), as individual MCP inbound tools
  • RBAC is available for MCP Inbound connections.
  • No limit to number automations (bots and processes) that you can run.
  • Streamable HTTP with API Key is supported.
Enterprise license Besides what is included in the Base license, the PRE/Automation Discovery Service is also available.