Keyword search picks the right tool for an AI agent 21% of the time. The router we built picks it 88%...
Switchboard selects the right MCP tool among 100+: accuracy 88% vs 21%, tokens -99.6%. For AI teams, decouples tool catalog from prompt budget: lower hallucination, reduced cost-per-query, scalable without reliability trade-off.
Keyword search picks the right tool for an AI agent 21% of the time. The router
we built picks it 88% of the time, while cutting the tokens spent describing
those tools by 99.6%. This is how we got there, including the parts we got
wrong first.
Architecture: Link
The Problem Model Context Protocol (MCP) lets an AI agent call structured tools instead of...
The Setup I've been building AI agents that use tools — reading files, running commands,...
Every MCP server pays a hidden tax: the moment an AI agent connects, your entire tools/list gets...
The Model Context Protocol (MCP) is how AI agents talk to tools. Claude Code, Cursor, Windsurf — they...
mcp2cli -> Save 96–99% of the tokens wasted on tool schemas every turn; caveman -> laude Code...
How to Build an MCP Style Routed AI Agent System with Dynamic Tool Exposure Planning, Execution, and Context Injection
