agentos
★ 682
vs
nanobot
★ 49.3k
agentos vs nanobot
agentos: AgentOS is an open-source TypeScript framework for agents with persistent cognitive memory, runtime tool forging and multi-agent orchestration across 13 LLM providers. Forged tools are tested, reviewed by an LLM judge and run in a node:vm context or a QuickJS WebAssembly sandbox.; nanobot: nanobot is an ultra-lightweight, self-hosted personal AI agent framework built in Python, offering a readable core for multi-agent delegation and automation. It supports various interfaces including WebUI, terminal, and chat apps, integrating tools, long-term memory, and OpenAI-compatible APIs.
01
TL;DR
agentosMulti-Agent · ★ 682
Build TypeScript agents that remember users across sessions
nanobotMulti-Agent · ★ 49.3k
When to choose:
- You want a lightweight, hackable Python personal AI agent framework with clean code, a WebUI, and built-in MCP client support.
- You prefer an easy-to-read, self-hosted agent core without the enterprise boilerplate of heavy agent frameworks.
When to skip:
- You require production-grade distributed state checkpointing, strict Pydantic type validation, or multi-role team SOPs; Pydantic AI or CrewAI offer more mature infrastructure.
- Your production stack is .NET or Go; Microsoft Agent Framework covers those runtimes.
02
Side-by-Side Comparison
Field
agentosnanobotCategory
Multi-Agent
Multi-Agent
Stars
★ 682
★ 49.3k
License
Apache-2.0
MIT
Install Command
npm install @framers/agentos
curl -fsSL https://raw.githubusercontent.com/HKUDS/nanobot/main/scripts/install.sh | sh
Updated
1d ago
1d ago
Open Source
Yes
Yes
Tags
agent-framework, agent-memory, agentic-ai
AI Agent Framework, Self-hosted, Python
03
Features
agentos01Persistent cognitive memory with decay and reconsolidation mechanisms
02Runtime tool forging with test cases and an LLM judge
03Six multi-agent orchestration strategies
04One dispatch interface across 13 LLM providers
05Optional HEXACO personality, guardrails and voice pipeline
nanobot01Persistent workflows: goals, memory, tools, and chat context survive long-running work.
02Chat-native reach: WebUI, API, Telegram, Feishu, Slack, Discord, Teams, email, and Mattermost.
03Model freedom: OpenAI-compatible APIs, local LLMs, image generation, search, and fallbacks.
04Small core: readable internals with MCP, memory, deployment, and automation built in.
05Own your stack: inspect, customize, self-host, and extend without a giant platform.
04
Use Cases
agentos↳Build TypeScript agents that remember users across sessions
↳Let agents create new tools safely when no existing tool fits
↳Orchestrate multiple agents in long-running sessions
nanobot↳Running long-horizon goals and scheduled automations.
↳Connecting to various chat applications like Telegram, Discord, Slack for AI interaction.
↳Exposing a Python SDK and OpenAI-compatible API for custom integrations and development.
↳Deploying as a long-running local or server-side agent gateway.
05
Best For
agentosTrendingHidden Gem
nanobotMost PopularEssential
FAQ
FAQ
What is the difference between agentos and nanobot?
Both agentos and nanobot are in the Multi-Agent category. agentos has 682 stars, while nanobot has 49.3k stars.
Which is better, agentos or nanobot?
The best choice depends on your use case. Choose agentos if Build TypeScript agents that remember users across sessions, and nanobot if Running long-horizon goals and scheduled automations..
Is agentos free or open source?
Yes, agentos is open source on GitHub (Apache-2.0).
Is nanobot free or open source?
Yes, nanobot is open source on GitHub (MIT).
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