Connect your data to your agents.

The interface between production databases and AI agents.

curl -fsSL /install | bash

The open source infrastructure you need.

Support everything from prototypes to multi-agent systems without changing your architecture.

Declarative Data Interfaces

Define the shape and intent of data access once, and let Hyperterse handle execution, validation, and exposure.

Agent-Ready by Design

Connect your data to AI agents through discoverable, callable tools—without exposing SQL, schemas, or credentials.

Zero-Boilerplate APIs

Turn queries into production-ready APIs with typed inputs, predictable outputs, and built-in documentation.

Single Source of Truth

Generate endpoints, OpenAPI specs, LLM-readable docs, and MCP tools from one configuration file.

Security as a Baseline

Keep raw SQL, connection strings, and internal errors fully contained within the runtime.

Database Independence

Work across PostgreSQL, MySQL, and Redis using a consistent, unified interface.

Fast Iteration

Update queries and schemas with immediate feedback during development.

Portable Deployment

Ship a self-contained runtime that moves cleanly from local development to production.

Get Started →

Stop doing it the hard way.

Define queries once, get a high-performant engine that is reliable, interpretable, and structured.

Without Hyperterse
  • × Build custom API endpoints for each query
  • × Write boilerplate validation and error handling
  • × Manually create OpenAPI documentation
  • × Build MCP tools from scratch for each agent
  • × Maintain llms.txt and agent skills manually
  • × Weeks of development and ongoing maintenance
With Hyperterse
  • ✓ Define queries once in a configuration file
  • ✓ Automatic input validation and type checking
  • ✓ OpenAPI specs generated automatically
  • ✓ MCP tools ready for any AI agent
  • ✓ llms.txt and agent skills auto-generated
  • ✓ Up and running in minutes
Learn more →

How it works

Full-featured engine with MCP endpoints, OpenAPI docs, input validation, and AI integration materials.

No code required - just define it and run it.

Input
Configuration File
Define queries in a simple configuration.
→
Process
Hyperterse
High-performance runtime server that generates endpoints automatically.
→
Output
REST + MCP
Agent-ready tools and literature

Frequently Asked Questions

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What is Hyperterse?

Hyperterse is a high-performance runtime server that transforms your database queries into RESTful API endpoints and MCP (Model Context Protocol) tools. Define queries in a simple configuration file, and Hyperterse automatically generates individual endpoints with full OpenAPI documentation, input validation, and AI integration.
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Is Hyperterse free?

Yes. Hyperterse is free and open source. You can self-host it on your own infrastructure at no cost. If you need any help, we offer enterprise support. Reach out to us at enterprise@hyperterse.ai
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How do I define queries?

Queries are defined in a simple configuration file (e.g., config.terse). You specify adapters (database connections), queries with SQL statements, and input parameters with their types. Hyperterse handles the rest—generating endpoints at POST /query/{query-name}, validating inputs, and creating documentation.
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Which databases are supported?

Hyperterse supports PostgreSQL, MySQL, and Redis out of the box. Each database has its own connector, and you can configure multiple database connections in a single Hyperterse instance.
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What is MCP and how does it work?

MCP (Model Context Protocol) is a standard for exposing tools to AI assistants and LLMs. Hyperterse automatically generates MCP-compatible tools for each query you define, allowing AI agents to execute database queries via JSON-RPC 2.0.
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Is my database connection secure?

Yes. Connection strings and raw SQL are never exposed to clients. Hyperterse acts as a secure gateway. Clients only interact with the generated API endpoints, not the underlying database directly.
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What documentation formats are generated?

Hyperterse auto-generates OpenAPI 3.0 specifications (available at GET /docs), markdown documentation at GET /llms.txt for LLM integration, and supports generating agent skills archives. All documentation is automatically kept in sync with your configuration.
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Do I need to write any code?

No. Hyperterse is configuration-driven. You write SQL queries in configuration files (like config.terse), and Hyperterse generates everything else. No boilerplate code, no ORM setup, no route handlers. Just define your queries and run the server.
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Is Hyperterse an ORM?

No. Hyperterse does not abstract away SQL. You write raw SQL queries directly in your configuration file. It focuses solely on query execution and API exposure, not database abstraction or migrations. Perfect for AI & LLM applications, API gateways, microservices, and rapid prototyping.