OpenAkita
Open-source multi-agent AI assistant with desktop app, IM channel integration, plugins, memory and sandboxed tool execution.
At a Glance
Self-hosted OpenAkita core released under the GNU AGPL v3 license; users supply their own LLM API keys (external cost).
Engagement
Available On
Listed Oct 2026
About OpenAkita
OpenAkita is an open-source, self-evolving AI assistant that coordinates multiple specialized agents to carry out tasks such as web research, file handling, desktop automation and scheduled jobs. It ships as a GUI desktop app (Windows, macOS, Linux) and can also be installed via pip or from source, and it can be reached through chat platforms such as Telegram, Feishu, WeCom, DingTalk and QQ.
What It Is
OpenAkita is a multi-agent AI assistant framework written in Python with a Tauri and React desktop client. You supply an LLM API key, and the assistant plans tasks, calls built-in tools (shell, files, browser, desktop, search, scheduler, MCP) and delivers results in chat. The README states setup is fully GUI-based, with a CLI also available (openakita init, openakita run, openakita serve).
How Multi-Agent and Organization Mode Work
An orchestrator decomposes a request and assigns it to specialized agents that work in parallel, with automatic handoff, failover and a delegation depth limit. Organization orchestration goes further: users design an org chart in the GUI where each node (CEO, CTO, marketing, etc.) is an independent agent with its own identity and memory, sharing information through a three-level blackboard, with message routing, heartbeat checks and deadlock detection.
Memory, Models and Self-Evolution
Memory has two modes: fragment memory with semantic and full-text recall, and an MDRM relational graph covering temporal, causal, entity, action and context links, with automatic routing between them. It supports 30+ LLM providers with failover, including Anthropic, OpenAI, DeepSeek, Gemini and local Ollama or LM Studio (the README notes small local models have limited tool-calling ability). The self-evolution routine performs daily self-checks, root-cause analysis of failures and automatic skill generation or installation.
Extensibility and Security
The plugin system offers eight plugin types, a three-tier permission model and lifecycle hooks, with fault isolation. A skill marketplace and an MCP client (stdio, HTTP, SSE) add further capabilities. A six-layer security model covers path zoning, confirmation gates, command interception, file snapshots, self-protection and OS-level sandboxes (bubblewrap, seatbelt, Windows Mandatory Integrity Control).
Current Status
The latest GitHub release listed is v1.27.42. The source is licensed under AGPL-3.0-only, while brand assets are covered separately by a trademark policy.
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Pricing
Open Source (AGPL-3.0)
Self-hosted OpenAkita core released under the GNU AGPL v3 license; users supply their own LLM API keys (external cost).
- Licensed under GNU Affero General Public License v3.0 (AGPL-3.0)
- Desktop app, Python package (pip install openakita[all]) and source code
- Bring your own LLM API key (external provider cost)
- Multi-agent, plugin system, 30+ LLM providers, 6 IM platforms, 89+ built-in tools
Capabilities
Key Features
- Multi-agent collaboration with parallel delegation and failover
- Organization orchestration with visual org chart and blackboard memory
- Plan mode with task decomposition and progress tracking
- ReAct reasoning engine with checkpoint/rollback
- 89+ built-in tools including shell, files, browser, desktop and scheduler
- Plugin system with 8 plugin types and 3-tier permissions
- 6-layer sandbox security
- Dual-mode memory with MDRM relational graph
- 30+ LLM providers with failover
- IM scan-to-bind for WeChat, Feishu and WeCom
- Skill marketplace and AI-generated skills
- MCP client integration
- Self-evolution with daily self-check
- Desktop, web and mobile access
- Token usage and tracing observability
