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Open Multi-Agent

Build AI agent teams in TypeScript with task DAG scheduling

TypeScript framework for multi-agent orchestration. Define AI agents with different roles, describe a goal, and the framework handles the rest. - Task DAG with topological scheduling — dependent tasks wait, independent ones run in parallel - Model-agnostic — mix Claude + GPT in one team - In-process — no subprocess overhead, serverless-ready - Agents communicate via MessageBus + SharedMemory MIT licensed, 520+ GitHub stars in 10 hours.

About Open Multi-Agent on Product Hunt

Build AI agent teams in TypeScript with task DAG scheduling

Open Multi-Agent was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #447 on the daily leaderboard. TypeScript framework for multi-agent orchestration. Define AI agents with different roles, describe a goal, and the framework handles the rest. - Task DAG with topological scheduling — dependent tasks wait, independent ones run in parallel - Model-agnostic — mix Claude + GPT in one team - In-process — no subprocess overhead, serverless-ready - Agents communicate via MessageBus + SharedMemory MIT licensed, 520+ GitHub stars in 10 hours.

Who hunted Open Multi-Agent?

Open Multi-Agent was hunted by JackChen. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

For a complete overview of Open Multi-Agent including community comment highlights and product details, visit the product overview.