Hyperterse
Hyperterse provides an open-source, declarative framework for building high-performance MCP tool servers that safely connect AI agents to production databases.
At a Glance
- AI Developers
- Software Engineering Teams
- Enterprise AI Operations
AI Tools by Hyperterse
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Hyperterse
DB to MCP API Server
Discussions
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Latest News
Hyperterse 2.0: A schema-first framework for building MCP servers directly on top of production databases
Hyperterse adds SQLite support for easier local development
Products & Services
An open-source, declarative framework for building Model Context Protocol (MCP) tool servers. It allows developers to expose database queries as secure tools for AI agents.
Market Position
Hyperterse positions itself as a faster, more declarative alternative to manually building MCP servers, focusing on developer productivity and security.
Leadership
Founders
Samrith Shankar
Samrith Shankar was previously Assistant Vice President of Technology at Dream11, a major fantasy sports platform in India. He also served as a Team Lead and Senior Software Developer at Media.net, focusing on advertising technology. He is a product-driven engineering leader with experience building and scaling high-traffic applications.
Executive Team
Samrith Shankar
Founder
Samrith Shankar was previously Assistant Vice President of Technology at Dream11, a major fantasy sports platform in India. He also served as a Team Lead and Senior Software Developer at Media.net, focusing on advertising technology. He is a product-driven engineering leader with experience building and scaling high-traffic applications.
Founding Story
Built by Samrith Shankar to solve the problem of safely providing AI agents access to production data without writing repetitive API endpoints and boilerplate validation.
Business Model
Revenue Model
Open-source with Enterprise support and licensing.
Pricing Tiers
Apache 2.0 license, self-hosted, full access to core features.
Enterprise support, custom plugins, and managed services.
Target Markets
- AI Developers
- Software Engineering Teams
- Enterprise AI Operations
- Exposing database queries to AI assistants
- Building production-grade multi-agent systems
- Secure gateway for agent-database interaction