This product was not featured by Product Hunt yet.
It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).

Product Thumbnail

Cosmonapse

An agent-to-agent protocol built for harness engineering

Open Source
Developer Tools
Artificial Intelligence
Visit WebsiteSee on Product HuntGithubTwitterReddit

Hunted byAqib KhanAqib Khan

Cosmonapse is an event-driven agent-to-agent protocol modeled on a nervous system. Agents are pure functions no base class, no lifecycle. Orchestration is a role, not a bottleneck: any node can dispatch, any node can react. Harnesses are built from typed signals instead of loops tool calls (incl. MCP), shared memory, human approval, and retries each compose as a node or hook around a stock model call. Same code scales from in-memory tests to NATS/Kafka. MIT. Python + TypeScript SDKs + CLI.

Top comment

Hey Product Hunt 👋 Every multi-agent framework I tried handed me one orchestrator class that had to know every agent, every step, every branch. Fine in the demo then you add a fourth agent or a human-approval step, and that file becomes the bottleneck every change routes through. And the "agent harness" everyone's building now? Usually the same god-object one level down: a while-loop that owns the model call, the tools, the memory, and the approvals. So I built Cosmonapse, an event-driven agent-to-agent protocol where a harness is a set of reactions, not a loop. The mental model is a nervous system: 🧠 Neuron — your agent, a pure (input) -> output function. No base class, no lifecycle. ⚡ Axon — turns output into a protocol-valid Signal. 🌿 Dendrite — receives and reacts. Any node can dispatch; any node can react. 🔗 Synapse — the bus. In-memory for tests → local broker in dev → NATS/Kafka in prod, same code. 💾 Engram — shared memory. Answered or approved once → recalled, not re-asked. Harness concerns decompose into typed signals: tools are TOOL_CALL/TOOL_RESULT (MCP plugs in the same way), human-in-the-loop is a clarification/permission signal any node can answer, and retries/routing/bidding are just nodes reacting to events. Add a capability by adding a node never by editing a loop. And the "orchestrator" is the same primitive as a worker (Cortex = Dendrite), so you run centralized or fully decentralized with zero code change. Apache -2.0 licensed. Python + TypeScript SDKs + cosmo CLI. pip install cosmonapse I'd love your take on two things: does the nervous-system naming help or get in the way? And how are you structuring your agent harness today?

Comment highlights

Typed signals instead of loops is a clever way to wire up retries and MCP tool calls, and the same harness running on NATS without rewriting feels like the kind of thing I'd actually reach for in a side project.

About Cosmonapse on Product Hunt

An agent-to-agent protocol built for harness engineering

Cosmonapse was submitted on Product Hunt and earned 0 upvotes and 2 comments, placing #42 on the daily leaderboard. Cosmonapse is an event-driven agent-to-agent protocol modeled on a nervous system. Agents are pure functions no base class, no lifecycle. Orchestration is a role, not a bottleneck: any node can dispatch, any node can react. Harnesses are built from typed signals instead of loops tool calls (incl. MCP), shared memory, human approval, and retries each compose as a node or hook around a stock model call. Same code scales from in-memory tests to NATS/Kafka. MIT. Python + TypeScript SDKs + CLI.

Cosmonapse was featured in Open Source (68.6k followers), Developer Tools (515.9k followers) and Artificial Intelligence (473.8k followers) on Product Hunt. Together, these topics include over 196.9k products, making this a competitive space to launch in.

Who hunted Cosmonapse?

Cosmonapse was hunted by Aqib Khan. 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.

Want to see how Cosmonapse stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.