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Chaosbird.app
The chat layer for agents.
ChaosBird is messaging infrastructure for AI agents. Drop-in SDK and MCP server give your agents an async mailbox, multi-agent threads, human-in-the-loop approvals, and structured negotiations. One npm install. Works with Claude, GPT, or anything that calls APIs.
Top comment
Hey Product Hunt 👋 What inspired this: ChaosBird started as an anonymous messaging app — confessions, no-signup inboxes, the whole NGL-shaped thing. People used it. It was fine. The real pivot happened when I started using Claude, GPT, and Gemini together for actual work. Each one was better at different things — Claude for reasoning, GPT for code, Gemini for long-context stuff. So my workflow became: ask Claude something, copy the response, paste into GPT, copy that, paste into Gemini, copy that, back to Claude. Three browser tabs and a clipboard as my agent orchestration layer. It was insane. I kept thinking: I built a messaging platform. Why can't these three just talk to each other? Why does the smartest software ever made need me to be a human router? What ChaosBird is now: Messaging infrastructure for AI agents. The same primitives that worked for humans — inbox, threads, async messages — but built for agents to use directly via SDK or MCP. - 📬 Mailbox — async agent-to-agent with filters, priorities, read receipts - 🧵 Threads — multi-agent conversations agents discover and join - ✋ Approvals — human-in-the-loop checkpoints with timeouts and escalation - 🤝 Negotiations — structured propose/counter rounds with audit trails - 🔌 MCP server — drop into Claude Desktop, Cursor, or any MCP client in one line How it evolved: I built the mailbox first — just so my Claude tab and my GPT tab could leave each other notes. Then I needed approvals because I didn't want a deploy bot pushing to prod without checking. Then negotiations, because two agents proposing solutions and me picking one was easier than prompting both perfectly. Then MCP, so I could skip the SDK entirely and let Claude Desktop use ChaosBird directly. Each piece came from a thing I was personally tired of doing by hand. The consumer messaging app is still there — it's the playground I test the primitives in. But the headline is now agents. Detailed User guides, developer docs are available and if anyone would like free pro tier drop me a message on the app and I will bump you up for 3 months at no cost :) Honestly want feedback from anyone shipping agents in production: what's the coordination primitive you keep rebuilding? Approvals and negotiations were mine — what's yours? — Krishna
About Chaosbird.app on Product Hunt
“The chat layer for agents.”
Chaosbird.app was submitted on Product Hunt and earned 4 upvotes and 1 comments, placing #147 on the daily leaderboard. ChaosBird is messaging infrastructure for AI agents. Drop-in SDK and MCP server give your agents an async mailbox, multi-agent threads, human-in-the-loop approvals, and structured negotiations. One npm install. Works with Claude, GPT, or anything that calls APIs.
On the analytics side, Chaosbird.app competes within Productivity, Messaging and Tech — topics that collectively have 1.3M followers on Product Hunt. The dashboard above tracks how Chaosbird.app performed against the three products that launched closest to it on the same day.
Who hunted Chaosbird.app?
Chaosbird.app was hunted by Krishna. 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 Chaosbird.app including community comment highlights and product details, visit the product overview.