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Architecture

How Agentbot is built. A reference for contributors, self-hosters, and anyone who wants to understand the system.

System Overview

Components

Frontend (Vercel)

Stack: Next.js 16 (App Router) + React 19 + Tailwind CSS v4 The web dashboard, onboarding flow, billing, and all user-facing pages. Deployed on Vercel with automatic Git-based deploys. Key directories:
  • web/app/ — Pages and API routes
  • web/app/api/ — Server-side API proxies (provision, billing, auth)
  • web/app/components/ — Shared UI components
  • web/app/lib/ — Utilities (auth, Stripe, security)

Backend (Render)

Stack: Express.js + TypeScript The core API server. Handles agent provisioning, deployments, A2A communication, and skill management. Key services:
  • POST /api/provision — Create new agents (public, no auth)
  • POST /api/deployments — Deploy agent containers (auth required)
  • GET /api/agents — List and manage agents
  • POST /api/ai/* — AI provider proxy (OpenRouter, Anthropic, etc.)
Protected endpoints use JWT auth middleware that verifies the token, attaches user context, and sets the RLS context on the database connection. See the auth API for details.

Worker service (Render)

A standalone background job processor built on BullMQ. It connects to the same Redis instance used by the backend and processes jobs from two queues: The worker also handles:
  • A2A message routing between agents
  • Webhook processing (Stripe, Telegram, Discord)
The worker listens for SIGTERM and drains in-flight jobs before shutting down.

Database (Neon PostgreSQL)

Stores:
  • User accounts and authentication
  • Agent configurations and metadata
  • Billing, subscriptions, and usage tracking
  • Skill marketplace data
  • A2A message history
All user-scoped tables are protected by PostgreSQL row-level security (RLS) policies. Each authenticated request sets a database-level user context so queries automatically return only the calling user’s data. Admin users bypass RLS and can access all rows. See Security for the full list of protected tables.

Cache (Redis)

Used for:
  • Rate limiting
  • Session management
  • Real-time agent status
  • A2A message queues
  • Webhook deduplication

AI Layer (Ollama + BYOK)

Two modes:
  • Ollama (self-hosted): Local inference for self-hosted deployments (Llama 3, Mistral)
  • BYOK: Users bring their own API keys for OpenRouter, Anthropic, OpenAI, Google, or Groq

A2A Bus (Agent-to-Agent)

Enables agents to communicate directly:
  • Request/response patterns
  • Fire-and-forget messages
  • Skill delegation between agents
  • Cross-tenant isolation enforced

Data Flow: Agent Provisioning

Data Flow: Agent Runtime

Self-Hosting

Agentbot is fully open source. To self-host:
  1. Frontend: Deploy web/ to Vercel or any Next.js-compatible host
  2. Backend: Run agentbot-backend/ on any Docker-capable server
  3. Worker: Run the worker entry point from agentbot-backend/ using Dockerfile.worker
  4. Database: Neon Postgres (free tier available) or any PostgreSQL 15+
  5. Redis: Any Redis 7+ instance
  6. AI: Ollama for local inference, or configure BYOK providers
See Installation for full setup instructions.

Tech Decisions