Stop writing MCP boilerplate for your AI Agents.

The "10-to-1" rule says we spend 10x more time reading code than writing it.

Yet, when connecting AI agents to databases, we are seeing developers drowning in manual boilerplate—writing endpoints, validation logic, and maintaining llms.txt files just to expose a simple query.

We built Hyperterse to kill that toil.

• Define: A simple config.terse file.

• Run: A high-performance server.

• Result: Auto-generated APIs, OpenAPI specs, and MCP tools that Claude or Cursor can use immediately.

We want to reduce time-to-production for AI tools by 90%.

If you could automate one part of your current AI-backend integration workflow, what would it be? Documentation generation? Input validation? Or the MCP configuration itself?

🔗 Github: https://github.com/hyperterse/hyperterse

🌏 Website: https://hyperterse.com

📖 Docs: https://docs.hyperterse.com

If you like the project, do give us a star ⭐ on GitHub. It helps us a lot!