LobsterAI

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TypeScriptMIT★ 6.2k

LobsterAI is an MIT-licensed desktop agent from NetEase Youdao that reads files, runs tools, drives a browser, edits Office docs, and takes tasks

App

Kind: desktop agent
Platform: macOS, Windows
Models: built-in models or bring your own API keys

From the project’s README

GitHub ↗

Written by the project's own authors, not by runchr. Snapshot taken 2026-11-03.

LobsterAI

The open-source desktop AI agent that does real work on your computer.

Describe a task in plain language. LobsterAI reads your files, runs tools, drives a browser,
edits Office documents, and hands back finished work — at your desk or from your phone.

English · 简体中文

Download · Quick start · Features · Build from source · Community

LobsterAI analyzing a spreadsheet and previewing the dashboard it built

Why LobsterAI

Most AI assistants stop at an answer. LobsterAI is built to finish the job.

It works where your work lives. Point it at a folder and it reads spreadsheets, writes documents, runs scripts, and browses the web, asking before anything sensitive.
You see the result, not just a reply. Web pages, charts, images, videos, PDFs, and Word, Excel, and PowerPoint files open in a side panel, ready to edit or share.
It keeps working when you step away. Schedule recurring jobs, or message your desktop agent from WeChat, Feishu, DingTalk, Telegram, and more.
It's yours. MIT-licensed, with sessions stored locally. Sign in to use the built-in models, or bring your own API keys.

Built by NetEase Youdao, LobsterAI is the first open-source desktop-grade agent from a major Chinese tech company.

Features

Native Office editing Open Word, Excel, and PowerPoint files right in the app. Edit by hand, or let the agent make changes live alongside you.	Kits, skills, and connectors Install role-based kits for engineering, design, finance, sales, and more, pick individual skills, or connect MCP servers.
Scheduled tasks Turn any prompt into a recurring job: morning briefs, end-of-day wrap-ups, weekly reports, and health checks.	Message it from anywhere Connect a chat app once, then send tasks to your desktop agent from your phone.

Everything in the box

Capability	What you get
Cowork sessions	Long-running tasks on local projects with streaming progress, a tool timeline, session forks, and approval prompts before file, shell, or network actions.
Artifacts and sharing	Live previews for HTML, SVG, Mermaid, images, video, Markdown, code, PDF, and Office files. Edit images in place and share results as a link.
Built-in browser	An in-app browser the agent can drive, with tabs, saved logins, and passkey support, for research and web workflows.
Computer use	Let the agent operate desktop apps on Windows x64 and macOS 13 or later.
Multiple agents	Create agents with their own identity, model, skills, and working folder, add ready-made experts from the Expert Plaza, and bind agents to chat channels.
Skills	Built-in skills for documents, spreadsheets, slides, PDFs, web search, browser automation, image and video generation, stock research, writing, email, and more. See `SKILLs/`.
MCP connectors	Add local or remote MCP servers from the marketplace, sign in with OAuth, and choose which tools each server exposes.
IM channels	WeChat, WeCom, DingTalk, Feishu/Lark, QQ, NetEase IM, NetEase Bee, POPO, Telegram, Discord, and email. Multi-instance platforms can route each bot to a different agent.
Desktop companion	A floating orb for quick tasks, screenshots, and actions on selected text, such as translating or reading aloud.
Memory and Dreaming	Durable memory files, plus optional scheduled "Dreaming" runs that consolidate what the agent learned, so preferences carry across sessions.
Models	Built-in models (DeepSeek, GLM, Kimi, Qwen, MiniMax, and more) after sign-in, or your own keys for OpenAI, Anthropic, Gemini, xAI, OpenRouter, Ollama, LM Studio, and any OpenAI-compatible endpoint.
Library	Every file your agents create, collected in one place across sessions, both local and shared.

Things to try

Scenario	Example prompt
Build a local tool	"I still track inventory and sales in Excel. Build a local inventory system that records purchases and sales, calculates stock and profit, and opens in my browser."
Analyze local data	"Use `product-growth.xlsx` to build a visual dashboard and summarize the main growth drivers."
Make a deck	"Research the AI agent market and turn the findings into a presentation."
Check a web dashboard	"Open the ads dashboard every morning, check spend and conversion anomalies, and summarize likely causes."
Screen documents	"Turn the resumes in this folder into a screening sheet and shortlist the strongest candidates against the JD."
Run scheduled work	"Every weekday at 9 AM, collect yesterday's AI news and send me a concise digest."

Quick start

Install LobsterAI. Download it from the official website, or get the latest release directly: macOS (Apple Silicon) · macOS (Intel) · Windows x64
Choose a model. Sign in to use the built-in models, or add your own API key under Settings → Custom Model.
Give it a task. Pick a working folder, describe what you want, and approve actions as it works. Generated files open in the side panel.
Go further. Install kits from Kits · Skills · Connectors, set up recurring work in Scheduled Tasks, or connect a chat app under Settings → IM Bot.

How it works

flowchart LR
  subgraph App["LobsterAI desktop app (Electron)"]
    UI["Renderer<br/>React · Redux · Tailwind<br/>sessions · artifacts · Office editors"]
    Main["Main process<br/>Cowork sessions · permissions · SQLite<br/>skills · MCP · IM · scheduler"]
    UI <-->|"preload IPC"| Main
  end
  Main <-->|"config sync · events"| Gateway["OpenClaw gateway<br/>bundled agent runtime"]
  Gateway --> Models["LLM providers"]
  Gateway --> Tools["Local tools<br/>files · shell · browser<br/>computer use · MCP servers"]
  Chat["Chat apps<br/>WeChat · Feishu · DingTalk · Telegram …"] <--> Gateway

Cowork is LobsterAI's product layer. It owns sessions, messages, permissions, artifacts, agents, and IM bindings, and stores them locally in SQLite.
OpenClaw is the agent runtime underneath. LobsterAI ships a pinned build, renders its config from app state, and translates its events into the Cowork stream.
The renderer is sandboxed with context isolation and talks to the main process only through the preload IPC bridge.

Build from source

Requirements: Node.js >=24.15.0 <25, npm >=11.17.0 <12, git, and pnpm.

git clone https://github.com/netease-youdao/LobsterAI.git
cd LobsterAI
npm install

# First run: fetches the pinned OpenClaw version into ../openclaw, builds the runtime, and starts the app
npm run electron:dev:openclaw

# Later runs, once the runtime exists
npm run electron:dev

CONTRIBUTING.md covers tests, linting, runtime options, packaging installers, and the project layout.

Security and privacy

Sessions, messages, and settings are stored locally in lobsterai.sqlite under the app's user data directory. Agent memory and runtime state live alongside it under openclaw/.
File operations, shell commands, and network access are permission-gated, and the agent asks before it acts.
Renderer windows run with context isolation, sandboxing, and no Node.js integration.