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.
ā”50-75% fewer tokens ā massive cost savings
š 3-5x faster inference ā better user experience
šÆ 95%+ accurate tool selection ā production-ready
Hybrid Ranking Engine:
ā¢ Keyword matching (<1ms) + semantic embeddings (50-100ms)
ā¢ Works with any MCP server
Use cases: autonomous agents, multi-step reasoning, cost optimization.
Contribute to ankitpro/cursor-rules-generator development by creating an account on GitHub.
Instead of manually writing rules for AI coding assistants, this tool analyzes your repository and generates structured rules.
Perfect for:
ā¢ AI coding workflows
ā¢ Large repositories with complex context
Key features:
ā¢ Automatic rule generation
ā¢ Open-source and extensible
Install:
npm install cursor-rules-generator-mcp
Try it with your repo and see how it improves AI-assisted coding.
