We just shipped Agent-Corex, and I want to share the story of why we built it.
The Problem We Faced:
Six months ago, we were building an LLM agent system that had access to ~200 different tools. We did what seemed logical: we dumped all of them into the system prompt.
Building LLM agents with 100+ tools? Context bloat kills performance and costs. Agent-Corex intelligently selects only the relevant tools your model actually needs.
⚡50-75% fewer tokens → massive cost savings
🚀 3-5x faster inference → better user experience
🎯 95%+ accurate tool selection → production-ready
Hybrid Ranking Engine:
• Keyword matching (<1ms) + semantic embeddings (50-100ms)
• Works with any MCP server
Use cases: autonomous agents, multi-step reasoning, cost optimization.
