Open Multi Agent
Description
TypeScript multi-agent orchestration engine — one runTeam() call from goal to result. Multi-model teams, auto task decomposition, parallel execution. 3 runtime dependencies.
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
README
Open Multi-Agent
The lightweight multi-agent orchestration engine for TypeScript. Three runtime dependencies, zero config, goal to result in one `runTeam()` call.
CrewAI is Python. LangGraph makes you draw the graph by hand. `open-multi-agent` is the `npm install` you drop into an existing Node.js backend when you need a team of agents to work on a goal together. Nothing more, nothing less.
[](https://www.npmjs.com/package/@jackchen_me/open-multi-agent) [](https://github.com/JackChen-me/open-multi-agent/stargazers) [](./LICENSE) [](https://www.typescriptlang.org/) [](https://github.com/JackChen-me/open-multi-agent/blob/main/package.json) [](https://codecov.io/gh/JackChen-me/open-multi-agent)
**English** | [中文](./README_zh.md)
What you actually get
- Goal to result in one call.
runTeam(team, "Build a REST API")kicks off a coordinator agent that decomposes the goal into a task DAG, resolves dependencies, runs independent tasks in parallel, and synthesizes the final output. No graph to draw, no tasks to wire up. - TypeScript-native, three runtime dependencies.
@anthropic-ai/sdk,openai,zod. That is the whole runtime. Embed in Express, Next.js, serverless functions, or CI/CD pipelines. No Python runtime, no subprocess bridge, no cloud sidecar. - Multi-model teams. Claude, GPT, Gemini, Grok, MiniMax, DeepSeek, Copilot, or any OpenAI-compatible local model (Ollama, vLLM, LM Studio, llama.cpp) in the same team. Run the architect on Opus 4.6, the developer on GPT-5.4, the reviewer on local Gemma 4, all i
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