Artificial Intelligence1 min read

Launch HN: Pomerado (YC F26) – Turn any website into an MCP for agents

By · Published by Everything Blog

In short

The platform generates usable APIs in about an hour by mapping out workflows using either direct HTTP requests or Playwright browser automation. A dedicated Guardian model supervises the build pipeline and runs synthetic tests to prevent overfitting before publishing clean input and output schemas. Once deployed, the resulting integrations run tasks in 5 to 30 seconds and automatically trigger repair jobs whenever a target site changes its layout.

Key points

  • Developers can access the technology via a free hosted tier or an open-source MIT-license…: Developers can access the technology via a free hosted tier or an open-source MIT-licensed release.
  • Deterministic handling of authentication and two-factor verification ensures raw user cre…: Deterministic handling of authentication and two-factor verification ensures raw user credentials remain hidden from models.
  • Early real-world deployments currently span automotive dealership software alongside pers…: Early real-world deployments currently span automotive dealership software alongside personal training management systems.

Sources checked by our analysis pipeline: 1

Hi HN, we’re Alan and Akshay from Pomerado (

https://pomerado.ai/). We connect your agents to any website by turning sites into deterministic, self-healing APIs in minutes, fully self-serve.

Agents are no longer limited by their intelligence, but rather by their ability to interact with systems. Airlines, banks, e-commerce, insurance portals, government sites, and legacy portals all lack APIs or MCPs and are common parts of personal assistant or business workflows. Agents instead rely on browser automation or computer use, which can be slow, expensive, and unreliable. And even if computer use were perfect, most companies have banned it out of security and compliance concerns.

We discovered this problem while tinkering with our own personal assistants. When OpenClaw came out, we wanted to “live our lives through our agents” and have them do everything for us. We soon found their usefulness was restricted by what tools they could connect to. For example, when trying to book flights, they fell back on computer use, which failed to checkout. These issues got magnified on repeated workflows, like searching many airlines at once.

Pomerado…

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