by fsistemas · Agent Tool · ★ 55
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sql2json Run SQL queries and get JSON (or CSV) on stdout — pipe it anywhere. connects to any SQLAlchemy-supported database, executes a query, and writes the results as JSON to standard output. No server, no framework, no boilerplate. Use cases Scheduled reports: run a cron job that pulls yesterday's sales and posts the JSON to a dashboard (Geckoboard, Grafana, etc.) Shell pipelines: pipe query results into , , or any CLI tool that speaks JSON AI agent data retrieval: let an LLM agent query your database with a single subprocess call — see AGENTS.md ETL glue: extract rows as JSON, transform with standard tools, load elsewhere Monitoring & alerting: script threshold checks against live database metrics Install SQLite works out of the box (it ships with Python). For PostgreSQL or MySQL, install the matching driver extra: Other databases work too — install any SQLAlchemy-supported driver (e.g. for MS SQL Server) alongside . Docker The image includes drivers for PostgreSQL
| Stars | 55 |
| Forks | 11 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 72.2503613308719/100 |
| Last Updated | 2026-07-01 |
| Created | 2019-12-21 |
| Platforms | cli, python |
| Est. Tokens | ~17k |
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sql2json is Python CLI tool to run queries against sqltatabases and convert the results to json, csv, excel in the command line or python program. Easy to use for Humans, automations, LLMS/Agents. It is categorized as a Agent Tool with 55 GitHub stars.
sql2json is primarily written in Python. It covers topics such as automation, cli, command-line-tool.
You can find installation instructions and usage details in the sql2json GitHub repository at github.com/fsistemas/sql2json. The project has 55 stars and 11 forks, indicating an active community.
sql2json is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to sql2json on Agent Skills Hub include MCP-PostgreSQL-Ops, slowql, AutoRedTeam-Orchestrator. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.