Nous Research's Hermes Agent Cuts Tool Token Overhead by 50% With Smart Loading

If you've ever connected more than a handful of MCP servers to an AI agent, you've felt the pain: every tool's JSON schema gets shoved into the model's context on every single turn, whether the model needs it or not. When you connect multiple MCP servers to an agent, every tool's JSON schema gets sent to the model on every turn, even if the model only needs one or two tools for a given task. Nous Research just shipped a fix for this in Hermes Agent, and the numbers behind it are hard to ignore.

The tax you've been paying without knowing it

The scale of the problem is bigger than most people realize. A Hermes deployment with five MCP servers and 34 tools shows average prompt sizes of 45,000 tokens per turn, with roughly 22,000 of those tokens -- around 50% -- being tool schema overhead alone. And that's a modest setup. Anthropic's own engineering data shows tool definitions can consume 134,000 tokens before optimization, with the "MCP Tools Tax" measured at 15,000 to 60,000 tokens per turn for typical multi-server deployments.

Beyond token cost, there's an accuracy problem. Large tool catalogs cause decision paralysis, and removing irrelevant schemas from context reduces false positives. Anthropic's evals show Claude Opus 4 improved from 49% to 74% accuracy, and Opus 4.5 improved from 79.5% to 88.1%, with Tool Search enabled on large tool catalogs. That's not a marginal improvement -- it's the difference between an agent that works and one that doesn't.

Progressive disclosure, not brute force

Tool Search is Hermes' opt-in progressive-disclosure layer for this problem. When activated, MCP and plugin tools are replaced in the model-visible tools array by three bridge tools, and the model loads each specific tool's schema on demand. Think of it like lazy loading for tool definitions: the agent only pays for what it actually uses.