Definition
An agent harness is the runtime and orchestration layer around an LLM that decides when to call tools, how to manage memory, and how to handle errors and retries across a multi-step task.
In Depth
Unlike simple LLM API calls, an agent harness turns a model into an autonomous worker by giving it a loop, a toolset, and state. Popular harnesses in 2026 include LangGraph, Hermes Agent from Nous Research, OpenClaw, Mastra, CrewAI, and Smolagents. The harness is the piece most responsible for whether an agent deployment succeeds in production: it manages token budgets, retry behavior, tool dispatch, and recovery from malformed outputs. A reliable search tool like Scavio pairs with any harness via MCP or a simple HTTP tool wrapper.
Example Usage
A team evaluating Hermes Agent against LangGraph compared how each harness handled a 40-step research task with Scavio as the search tool.
Platforms
Agent Harness is relevant across the following platforms, all accessible through Scavio's unified API:
- YouTube
Related Terms
MCP Connector
An MCP connector is an implementation of the Model Context Protocol that exposes tools and data resources to any MCP-com...
Sub-Agent
A sub-agent is a specialized agent spawned by a parent agent to handle a scoped task, allowing a larger workflow to be d...
Retry Storm
A retry storm is a failure mode in which many agents retry a soft-failing request simultaneously, cascading into rate-li...