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agent-framework46,386MIT

nanobot

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat a…

Updated Jul 30, 2026
Platforms
web
Pricing
free-open-source
Status
active
License
MIT

What it does

Core capabilities at a glance

  • Agent Framework
  • AI Agent
  • AI Agents
  • Chatbot
  • Chatops
  • Discord BOT
  • LLM Agents
  • Llms

Deep dive

The full breakdown - performance, comparisons, and setup

nanobot

nanobot is an agent framework - Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat apps.

Overview

🐈 nanobot is an ultra-lightweight, open-source, self-hosted personal AI agent framework written in Python. It runs in a WebUI, terminal, or chat apps and combines tools, long-term memory, MCP integrations, model routing, multi-agent delegation, scheduled automation, and an OpenAI-compatible API in a small, readable core.

  • Persistent workflows: goals, memory, tools, and chat context survive long-running work. - Chat-native reach: WebUI, API, Telegram, Feishu, Slack, Discord, Teams, email, and Mattermost. - Model freedom: OpenAI-compatible APIs, local LLMs, image generation, search, and fallbacks. - Small core: readable internals with MCP, memory, deployment, and automation built in. - Own your stack: inspect, customize, self-host, and extend without a giant platform.

Prerequisites: Python 3.11 or newer. Git is only needed for a source install. Published packages already include the WebUI; a current-source install needs 'bun' or 'npm' to build it.

If terminals, API keys, or config files are new to you, use the guided zero-background walkthrough in Start Without Technical Background instead of this compact README path.

nanobot is open-source, written primarily in Python, with 46,386 GitHub stars under the MIT license. The latest release is v0.3.0 (2026-07-25).

Key capabilities

From the project's documentation:

  • run in a browser WebUI or terminal
  • connect to Telegram, Discord, Slack, WeChat, Email, Mattermost, and other chat apps
  • use tools such as files, shell, web search, web fetch, MCP, cron, image generation, and subagents
  • keep session history and long-term memory through Dream
  • run long-horizon goals and scheduled automations
  • expose a Python SDK and OpenAI-compatible API for integrations

Install

A quick way to get started (always check the official docs for the latest):

pip install nanobot-ai

How it fits a local-AI stack

nanobot runs on your own hardware, so pair it with a model and a GPU sized to your needs. Use the VRAM calculator to pick a model that fits your card, and see what you can run for hardware guidance. Related agent frameworks in the directory:

Sources

Stats from GitHub, 2026-07-30.

Frequently asked

Quick answers to common questions

What is nanobot?

nanobot is a agent-framework tool for local AI workloads. Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat a…

Is nanobot free and open source?

Yes, nanobot has 46,386 GitHub stars and is licensed under MIT. You can self-host it for free on web.

What platforms does nanobot support?

nanobot runs on web.

What hardware do I need for nanobot?

The hardware requirements depend on which models you run. Check our hardware directory for compatible GPUs and systems. nanobot has 46,386 GitHub stars and an active community.

Does nanobot support GPU acceleration?

nanobot's GPU support depends on your specific setup. Check the documentation for details. For the best performance, pair it with an NVIDIA RTX 4090 or 5090.

What are the best alternatives to nanobot?

Popular alternatives include other agent-framework tools in our directory. Browse our full collection at /tool for comparisons, community reviews, and benchmark data to find the right fit for your workflow.

How much does nanobot cost?

nanobot is free-open-source. It is completely free and open source to self-host.

Pairs well with

Complementary tools, models, and hardware

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