#682 · Primary category: AI Agents & Automation
stackql
Query, provision and operate Cloud, SaaS, API and Model Context Protocol (MCP) resources through a unified SQL-based framework for humans and AI agents.
Project last updated:08/24/26
GitHub Stars
895
Forks
83
Contributors
25
License
MIT
Why we included this project
Teams wiring large language models into their cloud workflows usually struggle to give an agent safe, predictable access to real infrastructure. StackQL handles that by treating cloud, SaaS, and API providers as queryable datasets you address with ordinary SQL, then exposes the same capability through a Model Context Protocol server an agent can drive directly. Instead of teaching each assistant vendor-specific REST calls, you describe the desired state in a SELECT, INSERT, or UPDATE statement and StackQL transpiles it into the correct provider request. Platform engineers and SREs can run it from a CLI, as a service over the Postgres wire protocol, or as an MCP tool inside clients like Claude and VS Code. Every operation is expressed as a traceable query, which gives you a human-readable audit trail of anything an agent changed.
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