Connecting to an MCP server, such as the one used by GitHub, incurs a significant per-call cost before any actual tool execution. This overhead, which can be as high as $0.0302 per call on Claude Opus 4.8, is billed as input tokens for tool definitions. The cost varies dramatically between models, with Gemini 3.6 Flash being approximately 10 times cheaper than Claude Opus 4.8 for the same toolset. Explicit caching can reduce this overhead, but it does not apply to all tool configurations, and changes to even a single tool can re-bill the entire set. AI
IMPACT Developers must budget for significant per-call overheads when integrating tools with LLMs, with costs varying greatly by model choice.
RANK_REASON Analysis of tool overhead costs for AI models.
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →
