What an MCP server costs you in tokens

MCP server tool definitions create recurring token, latency, and accuracy costs because they remain in the model’s context on every turn, with Anthropic estimating that a typical five-server setup can consume about 55,000 tokens before a task begins and noting that tool-selection performance declines beyond roughly 30 to 50 available tools. Large intermediate data exchanged between direct tool calls further increases token use, can exceed context limits, and may introduce copying errors, so exposing a REST API’s many granular endpoints directly to agents is often inefficient. The recommended approach is to design a smaller, outcome-oriented tool surface that combines underlying API calls into common workflows, then use deferred loading and tool search for larger catalogs so the model loads only relevant definitions. For workflows involving large documents or datasets, code execution can keep data inside a sandboxed environment rather than routing it through the model context, though it requires operational safeguards. Servers can also reduce reconnect overhead by providing deterministic tool-list ordering and sensible catalog cache TTLs under the 2026-07-28 MCP revision, while newer headers support per-tool routing, metering, authorization, and rate limiting.

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