mcp-server

open-multi-agent: Seamlessly orchestrate AI tasks across any LLM

Founders can wire up flexible AI agent pipelines that auto‑plan task DAGs at runtime and run on Claude, ChatGPT, Gemini, DeepSeek or local models. Powered by open-multi-agent (7.0k+ GitHub stars).

From the repo · “TypeScript AI agent orchestration framework with dynamic workflows. Describe the goal, not the graph: a coordinator plans the task DAG at runtime and runs it on any LLM (Claude, ChatGPT, Gemini, DeepSeek, or local models).”

7,014 stars+13★ this week2,437 forksTypeScriptGuide quality 8/10 · reviewed Oct 19Updated 10/20/2026100% free · open source
What it does

Open-multi-agent is a TypeScript framework that allows dynamic AI agent orchestration with dynamic workflows, enabling the coordination of tasks across various large language models (LLMs) like Claude, ChatGPT, Gemini, DeepSeek, or local models

When to use it
  • •When you need to integrate multiple AI models into a single workflow
  • •When your startup requires dynamic task planning and execution using different LLMs
  • •When you want to run AI tasks on any available LLM, whether local or cloud-based
Ready-to-paste prompt
To run a task on the Claude LLM, use the following command: `npx ts-node runtime/index.ts --task my-task --model claude`
Heads up: Make sure to have the correct TypeScript version (14 or higher) installed, as open-multi-agent uses TypeScript features that are not compatible with lower versions
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

✅ Light setup

Installs with a command or two; your AI agent can do it for you.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/open-multi-agent && curl -fsSL https://workflowstacks.com/api/skills/open-multi-agent/claude-skill -o ~/.claude/skills/open-multi-agent/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

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How open-multi-agent: Seamlessly orchestrate AI tasks across any LLM works
Codeflow
Free to inspect

Open-multi-agent: Seamlessly orchestrate AI tasks across any LLM is a very large TypeScript project (~70k lines across 278 code files, plus 183 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit this month, MIT license, has a test suite.

Size
Very large codebase
~70k lines · 278 code files · days to read — use, don't read
Setup
One-command install
Installs like a normal app. Reading the code is optional.
Runs on
Node.js
No API keys detected
TypeScript 99%JavaScript 1%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    AGENTS.md
    The instructions the AI actually follows
  3. 3
    package.json
    Dependencies and the commands it exposes
  4. 4
    packages/core/README.md
    Inside packages/core/ — the main logic begins here
What's in each folder
packages/core/Core code — the actual logic461 files
docs/Documentation41 files
packages/release-bot/Package27 files
bench/Folder18 files
packages/otel/Package13 files
scripts/Helper scripts7 files
.github/CI / automation (GitHub Actions)27 files
READMEHas testsDocumentedCI checksMIT licenseUpdated this month
Quick Actions
Details
Creator
open-multi-agent
Language
TypeScript
Category
mcp-server
Published
3/31/2026

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