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Define your AI agents, tools, and entire data layer in one typed frogbot.config.ts — FrogBot boots the production agent backend for all of it. No routing code, no glue, no SaaS. That one file gives you a hosted UI, agent runtime, chat, skills, flows, integrations, model routing, file storage, authentication, REST and GraphQL APIs, and a job system — all in one MIT open-source TypeScript codebase you own and deploy anywhere.

Start here

Paste this prompt into Codex, Claude Code, Cursor, or another coding agent, and it sets up FrogBot for you:

Your coding agent checks your computer, creates the app with the FrogBot skill, and starts it.

Step-by-step setup

Go from nothing installed to your first chat, one plain-language step at a time.

Start with a coding agent

What the prompt asks your agent to do, and what it will ask you.

Installation

Create a project with npx create-frogbot-app@latest and choose its database and AI provider.

Concepts

The high-level building blocks: config, models, pieces, skills, agents, flows, plugins, and content directories.

Configuration

The frogbot.config.ts file that controls every part of the framework.

Deployment

Run your app in production with Docker or Fly.io.

What it gives you

  • An AI workspace UI for chats, agents, skills, flows, and connections
  • A file-based defaults system for skills, agents, MCPs, and flows
  • A pieces system for integrations (Slack, Gmail, Notion, GitHub, and more)
  • A piece connector layer that handles managed OAuth without per-piece OAuth apps
  • A job system for triggers, polling, scheduled flows, and waitpoints
  • Web, desktop, and browser extension clients sharing the same React app shell
    • A plugin system that extends the framework through config transforms