Docker for AI workers.
Build, compose, and deploy autonomous AI agents. Open-source infrastructure for the agent economy.
curl -fsSL agentbot.sh/install | bashOne command. Your agent is running on your machine — connected to Telegram, Discord, or WhatsApp. Your API key talks directly to your LLM provider. We don't touch the costs.
npx agentbot init # Create your first agent
npx agentbot dev # Run locally
npx agentbot deploy # Ship to production→ Agentbot Cloud for managed deployment
An agent is a Markdown file with YAML frontmatter:
---
name: researcher
description: Deep research agent for web analysis
model: openrouter/anthropic/claude-3.5-sonnet
tools: [bash, read, write, web, think, memory]
permissions:
bash: dangerous
read: safe
write: dangerous
---
# Researcher Agent
You are a deep research agent specializing in web analysis.That's it. Define your agent, give it tools, set permissions, write its instructions.
# Create your first agent
npx agentbot init
# Run locally
npx agentbot dev
# Deploy to Agentbot Cloud
npx agentbot deploy| Package | Description |
|---|---|
@agentbot/sdk |
Core SDK — agent parser, orchestration, plugins, types |
@agentbot/cli |
Developer CLI — init, dev, run |
@agentbot/plugins |
Official integrations — Discord, Telegram, email, browser |
Extend agents with capabilities:
import { discordPlugin, telegramPlugin } from '@agentbot/plugins'
// Plugins provide tools agents can use
const agent = new Agent({
tools: ['discord_send', 'telegram_send', 'email_send', 'browser_navigate']
})| Plugin | Tools |
|---|---|
| Discord | discord_send, discord_read |
| Telegram | telegram_send, telegram_webhook |
email_send, email_template |
|
| Browser | browser_navigate, browser_scrape, browser_screenshot |
Build your own plugin:
import { definePlugin, defineTool } from '@agentbot/sdk'
export const myPlugin = definePlugin({
name: 'my-integration',
description: 'Custom integration',
version: '0.1.0',
tools: [
defineTool({
name: 'my_tool',
description: 'Does something useful',
parameters: { input: { type: 'string', required: true } },
async execute(args, ctx) {
ctx.log(`Running with: ${args.input}`)
return { result: 'done' }
}
})
]
})- Research Agent — Web research and analysis
- Outreach Agent — Lead generation and cold messaging
- Content Agent — Blog posts, social media, documentation
- Crypto Analyst — Autonomous 24/7 market scanner
- Barista Agent — Morning motivation (5 AM survival mode)
- Multi-Agent Workflow — Compose agents into pipelines
Agent Definition (.md)
↓
Agent Runtime (SDK)
↓
Tool Orchestration (parallel reads, serial writes)
↓
Memory + Hooks
↓
Deploy (self-host or Agentbot Cloud)
| Field | Type | Required | Description |
|---|---|---|---|
name |
string | ✅ | Unique agent identifier |
description |
string | ✅ | Human-readable description |
model |
string | ✅ | LLM model to use |
tools |
string[] | ✅ | Available tools |
permissions |
object | ❌ | Per-tool permission overrides |
safe— Auto-approve (reads, searches, memory lookups)dangerous— Require user approval (writes, shell commands)destructive— Block entirely (rm -rf, DROP TABLE)
bash— Shell command executionread/write— File system operationsweb— Web search and fetchingthink— Internal reasoningmemory— Persistent memory storage
Agentbot automatically parallelizes read-only tool calls and serializes writes:
[read] [grep] [web_search] → parallel (Promise.all)
↓
[write file] → serial (wait for completion)
↓
[bash test] → serial (wait for completion)
↓
[read] [memory_search] → parallel
This gives you maximum throughput without race conditions.
Link your agent to a verified human identity via SelfClaw:
# Via dashboard (easiest)
open https://agentbot.sh/dashboard/verify
# Or directly
open https://selfclaw.ai/verifyVerified agents get a ✅ badge and are eligible for the marketplace.
# Clone and run locally
git clone https://github.com/Eskyee/agentbot-sdk
cd agentbot-sdk
npm install
npm run build
# Run with Docker
OPENROUTER_API_KEY=sk-... docker compose up
# Or run directly
npx agentbot run examples/research-agent/agent.mdFor production deployments with managed infrastructure:
- One-click deploy
- Hosted memory
- Dashboards and logs
- Team workspaces
- Secret storage
- Production uptime
- Premium model routing
We welcome contributions! See CONTRIBUTING.md for guidelines.
- Build agents and share them
- Create plugins for new integrations
- Improve the SDK and CLI
- Write documentation
- Report bugs
Agentbot is part of a growing ecosystem:
- $AGENTBOT — Community token on Base and Solana
- Agentbot Cloud — Managed deployment platform
- baseFM — Onchain radio platform
MIT
Agentbot — Docker for AI workers. Build once, deploy anywhere.