Author(s): Hoe shi Lee
Originally published on Towards AI.
Hermes AI Agent is gaining popularity these days as teams explore autonomous, workflow-driven systems for research, automation, and multi-step execution. I’ve used it for its structured planning, persistent memory, and ability to refine workflows through repeated runs.
The main issue shows up when workflows depend on multiple external systems. Execution itself is not the problem. The real friction comes from tool integration, where each API has its own authentication flow, response format, and failure behavior. This makes workflows harder to scale and maintain.
This is where MCP comes in. It introduces a standard way for agents to interact with external tools, removing the need to handle each integration separately.
