Instadash

AI agents generate structured data constantly — pricing tables, lead lists, log files, scraped research. The problem: the only place for it is a chat window. The table gets truncated, can't be filtered, and disappears when the session ends. Instadash gives that data a permanent home. One push from your agent — CLI, API, or MCP — creates a live, filterable, embeddable grid at a shareable URL. Both humans and agents can query it back. Built for: • MCP workflows (Claude Desktop, Cursor, Windsurf, Claude Code) • Firecrawl pipelines — pipe scraper JSON straight to a live grid • Human-in-the-Loop review — check rows before your agent acts on them • Log and research output — push thousands of rows without destroying your context window How it works: 1. Your agent produces JSON, CSV, or NDJSON 2. One push to Instadash (`cat data.json | instadash push --name leads`) 3. You and other agents get a live, queryable grid URL No database. No frontend. No schema setup. Private by default, public sharing when you want it. Free for public grids; $19/mo for private; $79/mo for the full MCP + webhooks + scheduled refresh tier. Try it: instadash.io