最佳开源 AI 智能体与个人 AI 助手
七款开源 AI 智能体对比:许可证、社区、成熟度以及它们到底有多开放,从 OpenClaw、Hermes Agent 到可以通读的小型代码库。
概览
| 机器人 | 许可证 | 聊天应用 | |||||
|---|---|---|---|---|---|---|---|
| OpenClaw | MIT | 39.4万 | 是 | 否 | Telegram, WhatsApp, iMessage, Discord, Slack | 免费 | |
| Hermes Agent | MIT | 26.2万 | 是 | 否 | Telegram, WhatsApp, iMessage, Discord, Slack | US$20/月起 | |
| nanobot | MIT | 5万 | 是 | 否 | Telegram, WhatsApp, Discord, Slack | 免费 | |
| ZeroClaw | MIT OR Apache-2.0 | 3.3万 | 是 | 是 | Telegram, WhatsApp, Discord | 免费 | |
| Agent Zero | MIT | 2万 | 是 | 是 | Telegram, WhatsApp | 免费 | |
| Rakazo | Apache-2.0 | 7538 | 是 | 是 | Telegram, WhatsApp, iMessage, Slack | US$10/月起 | |
| NanoClaw | MIT | 3.1万 | 是 | 是 | Telegram, WhatsApp, iMessage, Discord, Slack | 免费 |
检查清单
| OpenClaw | Hermes Agent | nanobot | ZeroClaw | Agent Zero | Rakazo | NanoClaw | |
|---|---|---|---|---|---|---|---|
| 开源许可证 | 是 | 是 | 是 | 是 | 是 | 是 | 是 |
| 支持本地模型 | 是 | 是 | 是 | 是 | 是 | 是 | 是 |
| 默认沙箱隔离 | 否 | 否 | 否 | 是 | 是 | 是 | 是 |
| 默认无遥测 | 否 | 是 | 是 | 是 | 否 | 是 | 否 |
| 接入你的聊天应用 | 是 | 是 | 是 | 是 | 是 | 是 | 是 |
| 你离开时也能工作 | 是 | 是 | 是 | 是 | 是 | 是 | 是 |
在这个领域,“开源”涵盖的范围很广。有些项目采用 MIT 许可证,背后没有公司在上面卖任何东西;有些是开放代码旁边配一个付费托管服务;还有少数虽然开源却几乎无人维护。这份排名关注的是开源本身:许可证允许你做什么、谁在支撑这些代码,以及这个项目明年是否还在推进。
我们如何排名
七款都是开源、可自托管的,也都能运行本地模型。我们考量了:
- 许可证。 对大多数读者来说,宽松许可证(MIT、Apache-2.0)排在 copyleft 之前,因为你可以修改和再分发而无需公开你的改动。
- 独立性。 一个没什么可卖的非营利组织或研究实验室,比一个用开源代码为付费层级引流的厂商更有保障,不过两者本身都不是问题。
- 社区与成熟度。 项目规模、发布节奏,以及维护者称其为 alpha、beta 还是稳定版。
- 可改造性。 要改动某样东西需要读多少代码。
- 本站的检查清单(见上表):沙箱、遥测、聊天应用和后台工作仍然计分,只是权重比我们的自托管排名低。
我们排除了 Khoj(采用 AGPL-3.0,自 2026 年 3 月以来没有发布新版本)和 OpenFang(自 2026 年 5 月以来没有任何提交)。
1. OpenClaw
OpenClaw 成为默认的开源 AI 智能体是有原因的。它采用 MIT 许可证,没有付费层级或托管服务,由非营利组织 OpenClaw Foundation 管理(主页)。它也是这份列表中社区规模最大的项目,而且遥遥领先(见上表),拥有 142 个官方插件和庞大的技能生态。
开源并不意味着默认安全:沙箱是关闭的,每日更新检查是开启的。在把它连接到真实账号之前,请先阅读 OpenClaw 安全吗?;如果你刚接触它,可以看看 OpenClaw 是什么。

2. Hermes Agent
Hermes Agent 采用 MIT 许可证,是这里第二大的项目。在两大项目中,它在数据方面最开放:默认无遥测,除非你选择 Nous Portal 作为模型提供商,否则一切都保存在 ~/.hermes 下。它的标志性功能是会自己编写并完善可复用的技能。
它在独立性上排第二:Nous Research 在免费代码之外还销售每月 20 美元起的 Nous Portal 订阅。你永远不必购买,但托管的网页搜索、图像和语音需要订阅或你自己的密钥。更多内容请见 Hermes Agent 是什么。

3. nanobot
nanobot 出自香港大学数据智能实验室,生来就是为了让人阅读:一个小巧的 Python 核心,采用 MIT 许可证,没有要卖的托管服务。它有 Python SDK 和 OpenAI 兼容 API,所以也可以作为你自己智能体的基础。内置的 WebUI 是这份列表中较好的之一。
取舍在于 shell 命令默认不在沙箱中运行。

4. ZeroClaw
ZeroClaw 采用 MIT 或 Apache-2.0 双许可证,以单个 Rust 二进制文件发布。仅从检查清单来看,它胜过上面所有项目:默认沙箱、无遥测。它在这里排第四,是因为社区比 OpenClaw 和 Hermes Agent 小得多,而且如果你打算改代码,Rust 的门槛比 Python 或 TypeScript 更高。

5. Agent Zero
Agent Zero 采用 MIT 许可证,是这份排名中最老的项目,自 2024 年 6 月起持续发布,并在 2026 年 8 月下旬到 11 月初之间发布了 v2.11 到 v2.15。它的社区 Plugin Hub 有 200 多个插件。
关于这个组织有两点需要了解:它是一家捷克小公司,而且项目为其 A0T 加密代币的持有者运营一个基于代币质押的模型代理(详情)。你可以忽略这个代理,接入任意提供商或本地模型。

6. Rakazo
Rakazo(我们开发的产品)采用 Apache-2.0 许可证,可以完全自托管。开放代码旁边是增加云端电脑的付费托管方案,所以在独立性上它和 Hermes Agent 处于同一位置。它满足检查清单上的每一项,但更年轻,并自称处于 beta 阶段。参见 Rakazo 评测。

7. NanoClaw
NanoClaw 采用 MIT 许可证,代码库刻意保持极小:一个主机进程加少量文件。这使它成为这里最易读的智能体。它在开放性上排最后,是因为它基于 Anthropic 的 Claude Agent SDK 构建,并且每一次定制都要用 Claude Code,所以尽管可以按智能体添加其他提供商,实际上它还是绑定在一个专有工具上。

许可证一览
| 许可证 | 智能体 |
|---|---|
| MIT | OpenClaw, Hermes Agent, nanobot, Agent Zero, NanoClaw |
| MIT 或 Apache-2.0 | ZeroClaw |
| Apache-2.0 | Rakazo |
这些许可证都允许你运行、修改和再分发代码,包括商业用途。你接入的模型是另一回事:开放权重的本地模型有各自的许可证,托管提供商也有各自的条款。
想从其他角度了解,请参阅最佳本地 AI 智能体和 OpenClaw 替代品。
精选推荐
Free, MIT-licensed personal AI agent that runs on your own computer and takes orders from WhatsApp, Telegram, iMessage, Slack and 20+ other chat apps.
The biggest ecosystem and every chat app, but sandboxing is off and telemetry is on by default.
访问 OpenClaw优点
- Free and MIT licensed, with no paid tier
- Runs on your own hardware, and state, memory and credentials stay there
- Works in 29 chat channels, including WhatsApp, Telegram, iMessage, Slack, Discord and Microsoft Teams
- Model-agnostic: 64 model and media providers, plus local models
- Large ecosystem of skills and 142 official plugins, and very active development
缺点
- Model costs are on you and can run high: testers and users have reported spending over $100 in a day with expensive models
- Sandboxing is off by default and the agent can run commands on the host unless you turn on approvals
- Setup and upkeep expect comfort with the command line; maintainers warn it is risky for non-technical users
- Broad access to email, messages and the system makes prompt injection and malicious third-party skills a real risk
Free, MIT-licensed AI agent from Nous Research that runs on your own machine or server, learns reusable skills, and chats with you on Telegram, Slack and more.
MIT licensed, no telemetry and lives in your chat apps, but commands aren't sandboxed by default.
访问 Hermes Agent优点
- Free and MIT licensed, and runs on hardware you control
- Writes and refines its own skills from experience, on top of persistent memory and cross-session search
- One gateway for 20+ chat platforms, including Telegram, Discord, Slack, WhatsApp, Signal and email
- Run several separate agents as profiles, each with its own model, memory and skills, and let them talk in group chats
- Model-agnostic, with a one-command import from OpenClaw
缺点
- Setup expects comfort with the command line and with running your own server
- Model costs are on you unless you use free models, and hosted web search, images and speech need a paid Nous Portal plan or your own keys
- iMessage needs a separate BlueBubbles server on a Mac
- No native mobile app; Android support is a command-line install through Termux
Free, MIT-licensed personal AI agent in Python with a browser UI and terminal app, scheduled tasks, memory, and chat on Telegram, Discord, Slack and more.
Small, readable Python with a good web UI and no telemetry, but shell commands aren't sandboxed by default.
访问 nanobot优点
- Free and MIT licensed, with a small Python core that is meant to be read and modified
- Polished bundled WebUI with projects, file diffs, an MCP app catalog and an automations calendar, plus a terminal UI
- Many chat channels, including Telegram, Discord, Slack, WhatsApp, WeChat, Feishu, Teams, Matrix and email
- Scheduled automations, long-running goals and a heartbeat that reports only useful results to your last chat
- Works with local models through Ollama, vLLM or LM Studio
缺点
- Shell commands are not sandboxed by default; the bubblewrap or macOS Seatbelt sandbox must be turned on, and Windows has none
- Model costs are on you, and voice messages need a separate transcription provider such as Groq or OpenAI
- No native mobile or desktop app; on a phone you use the WebUI in a browser or a chat app
- Missed scheduled runs are not replayed and interrupted subagent tasks are not relaunched after a restart
Personal AI agent in one Rust binary, MIT or Apache-2.0, with local or cloud models, 30+ channels, approval gates and an OS sandbox on by default.
Meets every check: one Rust binary, approval gates and an OS sandbox on by default, no telemetry, local models.
访问 ZeroClaw优点
- Safe defaults: the recommended profile asks before medium-risk actions, blocks high-risk ones, keeps files in the workspace and runs tools in an OS sandbox
- One small Rust binary with one config file, running on macOS, Linux, Windows and boards like a Raspberry Pi
- More than 30 channels, plus a web dashboard for chat, memory, config and cron
- Provider fallback chains, local models through Ollama, and cryptographic receipts for tool calls
- States plainly that it sends no telemetry and needs no cloud account or license server
缺点
- Slack, iMessage, Signal and several other channels are not in the standard release; you build from source with extra features to get them
- `zeroclaw quickstart` only sets up the model provider; channels and risk profiles mean editing the TOML config file
- The Docker sandbox backend isn't picked automatically under the default native runtime
- Model costs are on you
Free, MIT-licensed AI agent that runs in its own Docker Linux workspace with a terminal, browser and desktop apps, and chats on Telegram and WhatsApp.
Runs in its own Docker container with local models, but sends telemetry by default.
访问 Agent Zero优点
- Free and MIT licensed, with frequent releases (v2.11 to v2.15 between late August and early November 2026)
- The agent works in its own Linux workspace with a terminal, browser, desktop apps and LibreOffice, isolated from your computer unless you grant host access
- Web search runs through a local SearXNG instance, and speech-to-text and text-to-speech can run locally
- Projects keep memory, files, secrets, instructions and model choices separate per job, with workspace snapshots you can roll back
- Built-in Telegram, WhatsApp and email channels, a scheduler, MCP and a community Plugin Hub with 200+ plugins
缺点
- Needs Docker, and the container image is a full Linux desktop environment rather than a small service
- No built-in image generation; the docs show teaching it an image API yourself
- By default it checks for updates with Agent Zero's server, sending your version and a hashed instance ID
- Code runs in the same container as Agent Zero itself today; per-task sandboxes are only a v3 prototype
- WhatsApp works by linking a phone account through a Baileys bridge, which needs Node.js, rather than the official WhatsApp Business API
Open-source, self-hostable platform for persistent AI bots that each get a job, a computer, memory and routines, using the model you choose.
Our own product. Meets every check: Apache-2.0, sandboxed bot computers, no telemetry by default, any model you connect.
访问 Rakazo优点
- Open source (Apache-2.0) and fully self-hostable, including with local models
- Choice of model per bot, including existing Claude or ChatGPT subscriptions
- Bots keep working on schedules and triggers with their own cloud computer
- Approval controls over which actions a bot may take on its own
缺点
- Still in beta, with frequent releases
- You supply and pay for the model on the hosted plans, unless you buy Rakazo credits
- Telegram, WhatsApp and iMessage/SMS are only available when self-hosted
- More setup than a single chat app
Small, MIT-licensed OpenClaw alternative that runs each agent in its own Docker container and chats with you on WhatsApp, Telegram, Slack, Discord and more.
Every agent in its own container and a tiny codebase, but tied to Claude Code and sends setup diagnostics by default.
访问 NanoClaw优点
- Every agent runs in its own Docker container and sees only the folders you mount, so shell access stays off your host
- Small codebase (one host process and a handful of files) that you customize by having Claude Code edit your fork
- Agents never hold raw API keys: outbound calls go through a credential gateway with per-agent policies and rate limits
- Many chat channels, including WhatsApp, Telegram, Slack, Discord, iMessage, Teams, Matrix and email, with one or several agents per channel
- Scheduled tasks with optional script gates that skip waking the agent when there's nothing to do
缺点
- Built around Claude and Claude Code: customizing, debugging and adding channels all go through Claude Code
- Sends anonymous setup diagnostics unless you set NANOCLAW_NO_DIAGNOSTICS=1
- No config files by design, so every change means editing code in your own fork
- Needs Docker, and Windows only works through WSL2
功能
| OpenClaw | Hermes Agent | nanobot | ZeroClaw | Agent Zero | Rakazo | NanoClaw | |
|---|---|---|---|---|---|---|---|
| 联网搜索 | 是 | 是 | 是 | 是 | 是 | 是 | 是 |
| 图像生成 | 是 | 是 | 是 | 是 | 否 | 是 | 未知 |
| 语音模式 | 是 | 是 | 是 | 是 | 是 | 是 | 未知 |
| 文件上传 | 是 | 是 | 是 | 是 | 是 | 是 | 是 |
| 记忆 | 是 | 是 | 是 | 是 | 是 | 是 | 是 |
| 代你执行操作 | 是 | 是 | 是 | 是 | 是 | 是 | 是 |
| 应用集成 | 是 | 是 | 是 | 是 | 是 | 是 | 是 |
| 自主运行 | 是 | 是 | 是 | 是 | 是 | 是 | 是 |
| 主动给你发消息 | 是 | 是 | 是 | 是 | 是 | 是 | 是 |
| 可运行多个机器人 | 是 | 是 | 是 | 是 | 是 | 是 | 是 |
来源
OpenClaw
- OpenClaw homepage and Foundation section
- OpenClaw integrations: channels, providers and plugins
- openclaw/openclaw on GitHub (MIT, v2026.11.1)
- OpenClaw docs: Sandboxing (off by default)
- Wikipedia: OpenClaw
- Notebookcheck: OpenClaw can burn through hundreds of dollars per day
- OpenClaw docs: Memory overview
- OpenClaw docs: Automations
- OpenClaw docs: Chat channels
- OpenClaw docs: iMessage
- OpenClaw docs: Heartbeat, now a default Proactive check job
- OpenClaw docs: Multi-agent routing
- OpenClaw docs: Platforms (macOS, Windows, Linux, iOS and Android apps)
- OpenClaw docs: Tools (exec, browser, web search)
- OpenClaw docs: Audio and voice notes (inbound transcription)
- OpenClaw docs: Image and media support (inbound media)
- OpenClaw docs: Install (system requirements, installer script, npm, desktop apps, Docker)
- OpenClaw docs: One-click deploy on Railway
- OpenClaw docs: Usage telemetry and update checks (on by default, feature statistics opt-in)
- OpenClaw docs: Ollama provider (local models)
Hermes Agent
- NousResearch/hermes-agent on GitHub (MIT, v0.23.0)
- Hermes Agent homepage and Nous Portal pricing
- Hermes Agent documentation
- Hermes Agent docs: Profiles, running multiple agents
- Hermes Agent docs: Bot Mode
- Hermes Agent docs: Voice mode
- Hermes Agent docs: Vision and image paste
- Hermes Agent docs: iMessage via BlueBubbles
- Nous Research on X: Meet Hermes Agent (February 25, 2026)
- Hermes Agent docs: Session heartbeats and cron watchdogs
- Hermes Agent docs: FAQ (Is my data sent anywhere?)
- Hermes Agent docs: Installation (desktop packages, install script, Docker)
- Hermes Agent docs: Platform support (no Linux desktop package; PyPI installs unsupported)
- Hermes Agent docs: Docker setup
- Hermes Agent docs: Configuration (terminal backend defaults to local)
- Hermes Agent docs: Security (approval modes, optional container isolation)
- Hermes Agent docs: Local models
- Hermes Agent example config (shared metrics off by default)
nanobot
- HKUDS/nanobot on GitHub (MIT, v0.4.1, README)
- nanobot documentation
- nanobot release archive (officially launched February 2, 2026)
- nanobot docs: Chat apps
- nanobot docs: Providers and models (Ollama, vLLM, LM Studio)
- nanobot docs: Configuration (security, exec sandbox off by default, transcription, Langfuse)
- nanobot docs: Automations and heartbeat
- nanobot docs: Concepts (heartbeat delivery, subagent recovery)
- nanobot docs: Memory and Dream
- nanobot docs: Multiple instances
- nanobot docs: Deployment (Docker, services, Render)
- nanobot source: skills installer runs with DISABLE_TELEMETRY
ZeroClaw
- zeroclaw-labs/zeroclaw on GitHub (MIT OR Apache-2.0, v0.8.7, README)
- ZeroClaw website
- ZeroClaw docs: Sandboxing
- ZeroClaw source: risk presets (Balanced, recommended, has the sandbox on)
- ZeroClaw docs: Channels overview (default and standard release bundles)
- ZeroClaw docs: You own it (no telemetry)
- ZeroClaw docs: Docker and containers
- ZeroClaw source: tools (image generation, screenshot, web)
Agent Zero
- agent0ai/agent-zero on GitHub (MIT, README, safety model)
- Agent Zero releases (v0.2 in June 2024 to v2.15 on November 1, 2026)
- Agent Zero homepage
- Agent Zero docs: Installation (Launcher, A0 Install, Docker, local models)
- Agent Zero docs: VPS deployment (hardware requirements)
- Agent Zero model provider list
- Agent Zero update check code (version and hashed ID sent to api.agent-zero.ai)
- Agent Zero built-in Telegram integration plugin
- Agent Zero built-in WhatsApp integration plugin
- Agent Zero built-in plugins (scheduler, notify user, email, SearXNG search, Whisper STT, Kokoro TTS)
- Agent Zero docs: Memory guide
- Agent Zero docs: Agent Profiles
- Agent Zero docs: API integration (adding image generation yourself)
- Agent Zero v3: A Sneak Peek Inside the Sandbox (August 17, 2026)
- Agent Zero LLM API (Venice.ai proxy for A0T token stakers)
Rakazo
- Rakazo homepage
- Rakazo pricing
- Rakazo privacy policy
- Rakazo on GitHub (README and license)
- Rakazo changelog
- Rakazo releases
- Rakazo docs: Image and video generation
- Rakazo docs: Memory
- Rakazo docs: Connect apps
- Rakazo docs: Routines
- Rakazo docs: Chat apps
- Rakazo docs: Messaging apps (self-hosting)
- Rakazo docs: Bots and chats (add another bot, bot templates)
- Rakazo docs: Groups (several bots in one chat)
- Rakazo docs: Mobile app (notifications)
- Rakazo privacy policy (updated Sep 14, 2026)
- Rakazo privacy policy source on GitHub
- Rakazo docs: Logs and monitoring (product analytics off by default)
- Rakazo docs: Desktop app (run locally in Docker, updates)
- Rakazo docs: Docker computers
- Rakazo docs: Self-hosted models (Ollama, LM Studio)
- Rakazo Railway template setup guide






