A Cost Model for Token Consumption of Hypermedia and the Model-Context-Protocol in Agentic Loops

Abstract

Recent interest in LLM agents has created demand for agent-to-tool protocols, mechanisms by which agents can perform actions with remote systems. Two potential architectural approaches to these protocols are hypermedia, the architectural style underlying the World Wide Web, and Remote Procedure Calls (RPC). The Model Context Protocol (MCP) is a prominent example of the RPC approach currently being deployed for agent-to-tool communication. Hypermedia and MCP differ along two largely independent axes: how data is represented and how available actions are discovered. In this paper we present a cost model for token consumption in the concatenative reasoning and acting (ReAct) loop and show that it is quadratic in the number of tool-use cycles. Using this model we distinguish two possible sources of efficiency difference between hypermedia and MCP: representational efficiency, the per-observation token cost of a format, and architectural efficiency, the number of tool calls a discovery model requires to complete a task. We argue that both are plausible drivers of an efficiency gap and that the quadratic structure of the cost model makes the latter potentially decisive. We frame the question of which factor dominates as an open empirical problem.