The MCP ecosystem is growing fast. Developers are building extraordinary AI tools — but agents still can't reliably find and use them. Discovery is broken, and it's costing tool developers real revenue.
Thousands of AI tools now exist. Developers pour months into building them — fine-tuned capabilities, clean APIs, solid documentation. But when an AI agent needs to complete a task, it can't reliably find the right tool. Intent doesn't match to capability. Great tools sit idle.
If an agent can't find your tool, you don't get used. If you don't get used, you don't get paid. The problem isn't the quality of what's being built — it's that there's no intelligent layer connecting what agents need to what tools can do.
Inferventis sits between AI agents and the tools they need. When an agent has a task, we understand the intent — not just the keywords — and match it to the best available tool in our registry. We rank by semantic similarity, manifest quality, and historical performance.
Once the right tool is found, we handle everything else: routing the request, managing execution, processing payment, and returning the result. The agent gets what it needs. The tool developer gets paid.
We built Inferventis on a simple principle: if we don't bring you revenue, we shouldn't earn anything. So we don't charge upfront. No subscription, no listing fee, no platform tax on tools that don't get used.
It's the same model the App Store proved works at scale — we take a revenue split, only when a transaction happens. Our incentives are completely aligned with yours. The better we are at discovery and routing, the more revenue flows to tool developers, and the more we earn.
Think of us as the App Store for AI tools — except we're obsessed with making sure the right tool wins every time, because that's the only way the model works for everyone.