OpenAkita — Open-Source Multi-Agent AI Assistant
Not just chat — an AI team that gets things done.
- Source repo
- openakita/openakita
- Stars
- ★ 2k
- Last updated
- 25d ago
- License
- AGPL-3.0
- Primary language
- Python
- FA score
- 45/100 · Major gaps
At a glance
- How it runs
- Works with
- Universal · cross-platformOpenAI API · Claude API
- Cost
- Free software; you pay for model usage
- Setup effort
- Low · running in minutes
- You'll need
- Typical use
- Individual users: Install the desktop app, enter an API key, and ask AI to create a calculator, scrape weather data, etc., via natural language.
- Not a fit if
- Users wanting a standalone mobile app without a desktop backend
- Teams needing closed-source commercial integration (AGPL-3.0)
- Source review
- 45/100 · Major gaps
What does this agent do, and when should you use it?
OpenAkita is an open-source, all-in-one AI assistant framework with multi-agent collaboration and organization orchestration. It features an AgentOrchestrator, ReAct reasoning engine, Plan Mode, dual-mode memory (fragment and MDRM relational graph), a 6-layer sandbox security model, a plugin system (8 types, 3-tier permissions, 10 lifecycle hooks), and an MCP client. The desktop app (Tauri 2.x), web, and mobile clients connect to 6 IM platforms including Telegram, Feishu, WeCom, DingTalk, and QQ. Installation options include a GUI-based desktop installer, pip, or source. Usage ranges from CLI commands (like openakita run "Build a calculator") to scanning a QR code to bind your chat app and conversing with AI directly.
OpenAkita orchestrates multiple specialized agents (e.g., search, analysis, writing) to work in parallel on decomposed tasks, with automatic handoff and failover. Its Plan Mode breaks complex tasks into step-by-step plans with tracking, and the ReAct engine implements a Think→Act→Observe loop with rollback. It includes 89+ built-in tools across 16 categories (Shell, Files, Browser, Desktop, Search, Scheduler, MCP, etc.) to read/write files, execute commands, automate desktop apps, and run scheduled tasks. Via IM scan-to-bind (WeChat, Feishu, WeCom), users can send messages, images, files, and voice in their chat app, with AI responding intelligently. It also enables creating an "AI company" where hierarchical roles (CEO, CTO, CFO) operate autonomously with blackboard sharing, message routing, and heartbeat checks.
- Individual users: Install the desktop app, enter an API key, and ask AI to create a calculator, scrape weather data, etc., via natural language.
- Office workers: Bind Feishu or WeCom by scanning a QR code, then @AI to generate weekly reports, manage schedules, or summarize documents.
- Development teams: Use Plan Mode and multi-agent parallelism to automatically decompose a project like building a website into design, coding, and testing tasks.
- Business leaders: Build an 'AI company' with CEO, CTO, CFO roles, letting AI agents collaborate autonomously on market analysis, product planning, and more.
- Automation enthusiasts: Leverage 89+ tools and the plugin system, integrate MCP servers (e.g., GitHub, databases) to create custom automated workflows.
How do you install or deploy this agent?
Three options:
- Desktop app (recommended): Download the installer for Windows (.exe), macOS (.dmg), or Linux (.deb) from https://openakita.ai/download, run the onboarding wizard, and enter an API key from Anthropic or DeepSeek.
- pip: Run
pip install openakita[all], thenopenakita initfor the setup wizard. - Source:
git clone https://github.com/openakita/openakita.git,cd openakita, create and activate a virtual env,pip install -e ".[all]", thenopenakita init.
How do you use this agent?
After installation, run openakita for interactive chat, or openakita run "Build a calculator" for a single task. Use openakita serve to enable service mode for IM channels. In the desktop app, configure LLM endpoints, IM channels, skills, and scheduled tasks via the GUI. Once bound to an IM platform, @AI in the chat to converse. Advanced usage includes creating an organization (drag-and-drop org chart), installing plugins (from the marketplace or GitHub), and integrating MCP servers via the GUI or CLI.
What are this agent's strengths and limitations?
- True multi-agent collaboration and organization orchestration, enabling autonomous execution of complex task chains beyond simple chat.
- Support for 30+ LLM providers (Anthropic, OpenAI, DeepSeek, Qwen, etc.) with smart failover, avoiding vendor lock-in.
- 6-layer sandbox security (path zoning, confirmation gates, command interception, file snapshots, self-protection, OS-level isolation) for safe high-risk operations.
- Rich plugin system (8 types, 10 lifecycle hooks) with extensive extensibility, including 20 bundled AI-media plugins (e.g., video generation, dubbing) backed by 913 unit tests.
- Low barrier: fully GUI-based setup, ready in 5 minutes, no CLI required, and QR scan-to-bind for IM platforms, making it accessible to non-technical users.
- Relies on external LLM APIs; you must provide your own API key and incur usage costs. Local small models are not recommended.
- The mobile app is a companion client that requires a desktop backend; it cannot function fully standalone.
- Advanced features (e.g., organization orchestration, memory graph visualization) have a steep learning curve, and documentation is technical.
- AGPL-3.0 license may restrict commercial closed-source integration.
How does this agent compare with similar options?
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| OpenAkita — Open-Source Multi-Agent AI Assistant This agent | 45 · Major gaps | Desktop appFree + model costs | ★ 2k | 25d ago | Python | OpenAI API · Claude API |
| Agenvoy | 70 · Some gaps | CLIFree | ★ 457 | 2d ago | Go | Codex · Claude Code |
| SwarmClaw | 48 · Major gaps | Desktop appFree + model costs | ★ 692 | 3mo ago | TypeScript | Codex · Claude Code · OpenAI API · Claude API |
| Agent Swarm | 47 · Major gaps | Agent plugin / skillFree + model costs | ★ 904 | today | TypeScript | Codex · Claude Code |
How does FollowAgents rate this agent?
Why each dimension lost points
Evidence shows permission model (3-tier), confirmation gates, path zoning, command interception, file snapshots, self-protection, OS sandbox, but mostly README claims without implementation details or config examples, so each criterion gets 1. Deductions: lack of code-level evidence, and no indication of least-privilege defaults.
Self-consistency: README mostly consistent with pyproject.toml and requirements.txt, but websockets version mismatch (16.0 vs <16.0) in requirements.txt. Dependency availability: dependency list complete but no pinned versions or checksums, supply chain risk. Failure messages: no examples of error handling or user prompts.
Audience and scenarios: README clearly targets first-time users and developers, with multiple usage scenarios. Capability boundaries: lists 89+ tools and 8 plugin types but no specific limitations. Trigger precision: no detailed trigger mechanisms for commands or skills. Environment fit: supports multiple platforms and LLMs but lacks system requirements details.
Information architecture: README well-structured with TOC and sections. Install notes: multiple installation methods but no troubleshooting. Naming stability: version number present but no naming conventions. Examples and FAQ: examples present but no FAQ. Known limitations: not explicitly listed. License: AGPL-3.0 but no compatibility notes. Versioning/changelog: version number but no CHANGELOG. Maintenance responsibility: security contact email but no clear maintainer.
Output usability: describes various output forms but no actual output examples. Marginal value: feature-rich but no comparison with alternatives. Cost-benefit: no performance or resource consumption data.
Claim traceability: README claims not linked to specific code or docs. Cross-source corroboration: only README, no other sources. Fact-inference separation: no clear distinction between facts and inferences.
- Dependency version inconsistency: websockets version in requirements.txt conflicts with pyproject.toml, may cause installation issues.
- Security features are mostly claims without implementation details; review actual code recommended.
- No CHANGELOG provided, version changes not transparent.
Recent releases
Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.
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v1.27.42 v1.27.42 [稳定版]
Release notes excerpt
v1.27.42 更新日志 本次重点完善 OpenAkita 账号、资源市场与 SkillHub，引入云知识库连接能力，并持续改善组织任务、记忆管理、启动速度和桌面及移动端体验。 重要变化 - OpenAkita 账号正式接入桌面端 - 可直接从桌面侧边栏登录并查看账号状态；登录信息会及时同步，桌面、网页和移动端之间的授权衔接也更加顺畅。 - 资源市场安装流程全面升级 - 支持从市场页面或专属链接发起安装，安装前可确认版本与所需权限，安装时可查看实时进度；切换页面后，任务仍可在后台继续并随时查看。 - SkillHub 搜索与安装 - 现在可以搜索 SkillHub 中的技能，并通过经过校验的流程安全安装，无需手动下载和复制文件。 - 新增云知识库连接 - 可在桌面端管理只读云知识库，并按照设定的优先级查找内容，让回答更容易利用已有资料，同时不会改动原始知识库。 - 组织任务更加可靠 - 不同会话中的组织任务互不干扰，任务进度可及时同步到 IM 会话；每个成员也能按配置使用合适的模型。 新增功能与改进 账号与资源市场 - 新增 OpenAkita 账号登录、设备授权和状态同步，并提供中英文授权结果页面。 - 支持桌面端、移动端和远程网页之间安全地接续登录与安装请求。 …View on GitHub ↗ -
v1.27.38 v1.27.38 [稳定版]
Release notes excerpt
v1.27.38 更新日志 本次稳定版重点改善了多会话任务处理、任务结果交付和本地插件安装体验。同时优化了对助手回复的判断方式，减少不必要的提示和重试，让日常使用更加稳定顺畅。 重要变化 - 多个会话互不干扰 — 在不同会话中同时运行组织任务时，各会话会独立处理。一个会话中的任务、等待状态或取消操作，不会再影响其他会话。 - 任务结果交付更可靠 — 任务完成后，生成的文件能够更准确地显示和提供下载；遇到无法继续处理的问题时，也会给出更清楚、更有帮助的提示。 - 本地插件安装更方便 — 在插件安装页面新增文件夹选择按钮，可直接通过系统窗口选择本地插件目录，无需手动输入或复制完整路径。 - 回复处理更加准确 — 优化了对助手回复内容的判断，减少普通文字被误认为已执行操作的情况，避免由此产生的错误提醒和重复尝试。 问题修复与体验优化 - 修复多个会话同时运行组织任务时，可能互相阻塞或误取消的问题。 - 修复部分任务完成后，生成文件未能正确显示或下载的问题。 - 改进任务异常时的提示信息，帮助用户更快了解问题并采取下一步操作。 - 减少因回复措辞触发的错误判断，让任务执行过程更加自然稳定。 - 为本地插件目录选择功能补充中英文界面提示。 --- What's Changed in v1.27.38 …View on GitHub ↗ -
v1.27.37 v1.27.37 [稳定版]
Release notes excerpt
v1.27.37 更新日志 本次稳定版汇总自 v1.27.35 以来的改进：内置插件可更安全地使用您在 OpenAkita 里配置好的大模型，并在设置页提供统一的模型选择；同时修复了 IM 渠道图片同步到桌面端不够及时的问题。 重要变化 - 插件统一使用 OpenAkita 已配置模型 - Word Maker、Excel Maker、PPT Maker，以及剪辑、字幕、漫画、调研等多个内置插件，在做文本分析、规划与润色时，会走您在 OpenAkita 中配置并选中的模型，不再各走一套零散调用方式。 - 插件设置页可选择模型 - 多个内置插件的设置界面增加了经过校验的模型选择器，可直接挑选 OpenAkita 里已可用的端点/模型，配置更直观。 - IM 镜像图片实时显示 - 飞书、Telegram 等渠道成功发出图片后，对应桌面会话会尽快同步显示，不必手动刷新或重开对话。 新增功能与改进 插件与模型 - 为内置插件提供统一的大模型调用入口：按您在 OpenAkita 中配置的端点与故障切换策略来请求模型，调用更稳妥。 - Word / Excel / PPT 等文档类插件的规划与文本相关流程，改为使用上述统一模型选择。 - 剪辑、字幕、电商图、财务、视频、调研等插件的文本分析类能力，同步接入统一模型调用。 …View on GitHub ↗