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Benchmark Comparison Results

Benchmarks run: January 2026

Scenario: Impact of tool usage - one-shot

With 18 MCP servers loaded, multiple-mcp consumes 23x more input tokens (46,130 vs 1,999) than OneTool for the same task. This translates to 18x higher cost (2.34¢ vs 0.13¢) and 2x slower execution (12s vs 6s). The token overhead comes from sending all tool definitions with every request—a cost that scales with the number of configured servers regardless of which tools are actually used.

Task in out tools time cost result
compare:base 33 239 0 5s 0.07¢ FAIL
compare:mcp 1520 98 2 7s 0.11¢ PASS
compare:multiple-mcp 46130 125 2 12s 2.34¢ PASS
compare:onetool 1999 95 1 6s 0.13¢ PASS
compare:onetool-proxy 4654 188 3 11s 0.29¢ PASS

Scenario: Impact of tool usage - multi-turn

Multi-turn conversations amplify the token overhead. Over 3 turns, multi-mcp accumulates 28x more input tokens (146,387 vs 5,152) and costs 24x more (7.35¢ vs 0.30¢). The gap widens because MCP re-sends all tool definitions on every turn, while OneTool maintains a single consolidated interface.

Developer monthly impact (20 working days, ~10 conversations/day, ~10 turns each, Claude Opus 4.5 @ $5/M input): - multi-mcp: ~100M tokens, ~$500/month - onetool: ~3M tokens, ~$15/month - Waste: ~97M tokens/month (~$485 in pure overhead)

Task in out tools time cost result
compare:multi-mcp 146387 88 2 17s 7.35¢ PASS
compare:onetool 5152 158 2 10s 0.30¢ PASS

Assumptions

  • Benchmark model: google/gemini-3-flash-preview
  • multi-mpc has the following MCP servers: package-version, brave-search, context7, github, fetch, sequential-thinking, filesystem, memory, plantuml, excel, ripgrep, gemini-grounding, chunkhound, mcp-alchemy, magic, supabase, railway