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Agentbot

Docker for AI workers.

Build, compose, and deploy autonomous AI agents. Open-source infrastructure for the agent economy.

curl -fsSL agentbot.sh/install | bash

One 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

What is an Agentbot Agent?

An agent is a Markdown file with YAML frontmatter:

---name: researcherdescription: Deep research agent for web analysismodel: openrouter/anthropic/claude-3.5-sonnettools: [bash, read, write, web, think, memory]permissions:
bash: dangerousread: safewrite: 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.

Quick Start

# Create your first agent
npx agentbot init
# Run locally
npx agentbot dev
# Deploy to Agentbot Cloud
npx agentbot deploy

Packages

PackageDescription
@agentbot/sdkCore SDK — agent parser, orchestration, plugins, types
@agentbot/cliDeveloper CLI — init, dev, run
@agentbot/pluginsOfficial integrations — Discord, Telegram, email, browser

Plugins

Extend agents with capabilities:

import{discordPlugin,telegramPlugin}from'@agentbot/plugins'// Plugins provide tools agents can useconstagent=newAgent({tools: ['discord_send','telegram_send','email_send','browser_navigate']})
PluginTools
Discorddiscord_send, discord_read
Telegramtelegram_send, telegram_webhook
Emailemail_send, email_template
Browserbrowser_navigate, browser_scrape, browser_screenshot

Build your own plugin:

import{definePlugin,defineTool}from'@agentbot/sdk'exportconstmyPlugin=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}},asyncexecute(args,ctx){ctx.log(`Running with: ${args.input}`)return{result: 'done'}}})]})

Examples

Architecture

Agent Definition (.md)
↓
Agent Runtime (SDK)
↓
Tool Orchestration (parallel reads, serial writes)
↓
Memory + Hooks
↓
Deploy (self-host or Agentbot Cloud)

Agent Spec

Frontmatter Fields

FieldTypeRequiredDescription
namestringUnique agent identifier
descriptionstringHuman-readable description
modelstringLLM model to use
toolsstring[]Available tools
permissionsobjectPer-tool permission overrides

Permission Levels

  • safe — Auto-approve (reads, searches, memory lookups)
  • dangerous — Require user approval (writes, shell commands)
  • destructive — Block entirely (rm -rf, DROP TABLE)

Built-in Tools

  • bash — Shell command execution
  • read / write — File system operations
  • web — Web search and fetching
  • think — Internal reasoning
  • memory — Persistent memory storage

Orchestration

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.

Verify Your Agent

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/verify

Verified agents get a ✅ badge and are eligible for the marketplace.

Verification Guide

Self-Host

# 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.md

Agentbot Cloud

For production deployments with managed infrastructure:

  • One-click deploy
  • Hosted memory
  • Dashboards and logs
  • Team workspaces
  • Secret storage
  • Production uptime
  • Premium model routing

agentbot.sh

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Ways to Contribute

  • Build agents and share them
  • Create plugins for new integrations
  • Improve the SDK and CLI
  • Write documentation
  • Report bugs

Ecosystem

Agentbot is part of a growing ecosystem:

License

MIT


Agentbot — Docker for AI workers. Build once, deploy anywhere.

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Docker for AI workers. Build, compose, and deploy autonomous AI agents.

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