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AigenLabs Agent

The self-improving AI agent built by AigenLabs. The only agent with a built-in learning loop — it creates skills from experience, improves them during use, nudges itself to persist knowledge, and builds a deepening model of who you are across sessions.

Install​

Desktop app setup​

AigenLabs Desktop setup is currently guided. Contact AigenLabs for the customer install command for your operating system. The commands below are for command-line installs.

Without AigenLabs Desktop:​

For a command-line only install without AigenLabs Desktop, run:

Linux / macOS / WSL2 / Android (Termux)​

curl -fsSL https://docs.aigenlabs.vn/install.sh | bash

Windows (native)​

Run in powershell:

iex (irm https://docs.aigenlabs.vn/install.ps1)

See the full Installation Guide for what the installer does, the per-user vs root layout, and Windows-specific notes.

Fastest path to a working agent

After installing, run aigenlabs setup to choose your model provider, enable only the tools you need, and verify the agent with a clean first conversation.

What is AigenLabs Agent?​

It's not a coding copilot tethered to an IDE or a chatbot wrapper around a single API. It's an autonomous agent that gets more capable the longer it runs. It lives wherever you put it — a $5 VPS, a GPU cluster, or serverless infrastructure (Daytona, Modal) that costs nearly nothing when idle. Talk to it from Telegram while it works on a cloud VM you never SSH into yourself. It's not tied to your laptop.

🚀 InstallationInstall in 60 seconds on Linux, macOS, WSL2, or native Windows
📖 Quickstart TutorialYour first conversation and key features to try
🗺️ Learning PathFind the right docs for your experience level
⚙️ ConfigurationConfig file, providers, models, and options
💬 Messaging GatewaySet up Telegram, Discord, Slack, WhatsApp, Teams, or more
🔧 Tools & Toolsets60+ built-in tools and how to configure them
🧠 Memory SystemPersistent memory that grows across sessions
📚 Skills SystemProcedural memory the agent creates and reuses
🔌 MCP IntegrationConnect to MCP servers, filter their tools, and extend AigenLabs safely
🧭 Use MCP with AigenLabsPractical MCP setup patterns, examples, and tutorials
🎙️ Voice ModeReal-time voice interaction in CLI, Telegram, Discord, and Discord VC
🗣️ Use Voice Mode with AigenLabsHands-on setup and usage patterns for AigenLabs voice workflows
🎭 Personality & SOUL.mdDefine AigenLabs' default voice with a global SOUL.md
📄 Context FilesProject context files that shape every conversation
🔒 SecurityCommand approval, authorization, container isolation
💡 Tips & Best PracticesQuick wins to get the most out of AigenLabs
🏗️ ArchitectureHow it works under the hood
❓ FAQ & TroubleshootingCommon questions and solutions

Key Features​

  • A closed learning loop — Agent-curated memory with periodic nudges, autonomous skill creation, skill self-improvement during use, FTS5 cross-session recall with LLM summarization, and Honcho dialectic user modeling
  • Runs anywhere, not just your laptop — 6 terminal backends: local, Docker, SSH, Daytona, Singularity, Modal. Daytona and Modal offer serverless persistence — your environment hibernates when idle, costing nearly nothing
  • Lives where you do — CLI, Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Mattermost, Email, SMS, DingTalk, Feishu, WeCom, Weixin, QQ Bot, Yuanbao, BlueBubbles, Home Assistant, Microsoft Teams, Google Chat, and more — 20+ platforms from one gateway
  • Built for operators — Created by AigenLabs as a practical agent runtime for real work. Works with OpenRouter, OpenAI-compatible APIs, OAuth providers, local models, or any custom endpoint
  • Scheduled automations — Built-in cron with delivery to any platform
  • Delegates & parallelizes — Spawn isolated subagents for parallel workstreams. Programmatic Tool Calling via execute_code collapses multi-step pipelines into single inference calls
  • Open standard skills — Compatible with agentskills.io. Skills are portable, shareable, and community-contributed via the Skills Hub
  • Full web control — Search, extract, browse, vision, image generation, and TTS with provider choices for direct keys, local backends, or managed gateways
  • MCP support — Connect to any MCP server for extended tool capabilities
  • Research-ready — Batch processing, trajectory export, RL training with Atropos. Built by AigenLabs — the lab behind AigenLabs, Nomos, and Psyche models

For LLMs and coding agents​

Machine-readable entry points to this documentation:

  • /llms.txt — curated index of every doc page with short descriptions. ~17 KB, safe to load into an LLM context.
  • /llms-full.txt — every doc page concatenated into a single markdown file for one-shot ingestion. ~1.8 MB.

Both files also resolve at /docs/llms.txt and /docs/llms-full.txt. Generated fresh on every deploy.