How MCP Improves External Tooling in Hermes AI Agent Workflows

Editor's take

Hermes AI, an open-source agent framework, has introduced a new component called MCP (Multi-Call Planner) to enhance its ability to interact with external tools. This development addresses a significant bottleneck in agent design: the sequential execution of tool calls, which can be inefficient for complex tasks.

The improvement is crucial for practical AI agent deployment, enabling faster and more sophisticated task completion. By allowing agents to plan and execute multiple tool interactions in parallel or in a more optimized sequence, Hermes can better tackle real-world problems that require invoking various APIs or services, a common challenge for frameworks like LangChain or Auto-GPT.

Future developments to monitor include the actual performance gains in benchmarked agent tasks and the framework's adoption rate by developers. It will also be interesting to see if MCP's approach influences the design of tool-use strategies in other agent architectures, potentially setting a new standard for efficiency.