Pomerado Launches Platform to Convert Websites into Agent-Ready MCPs
Pomerado enables developers to transform legacy websites into deterministic APIs for AI agents.
1Bridging the Agent Gap
Pomerado addresses the critical bottleneck where AI agents struggle to interact with legacy websites lacking formal APIs. Founders Alan and Akshay developed a platform that converts standard websites into deterministic, self-healing Model Context Protocol (MCP) tools. This transition allows agents to move beyond unreliable browser automation and expensive computer use methods.
2Deterministic API Generation
The platform functions by having an agent perform a task once, recording the HTTP requests or Playwright scripts required to navigate the site. This initial execution establishes a repeatable pattern. A secondary Guardian model then reviews these calls against safety guardrails, ensuring the resulting API schema is generalized, stable, and ready for production.
3Handling Complex Authentication
Security and compliance are managed through a deterministic sign-in process that prevents the model from accessing raw user credentials. The system supports 2FA by allowing users to store TOTP seeds or link accounts to a Pomerado phone number. This ensures that automated workflows remain secure while maintaining necessary access to restricted portals.
4Self-Healing Maintenance Cycles
When a website structure changes, such as a renamed button or modified input field, Pomerado initiates an automated maintenance job. This process repairs broken steps and can even expand functionality based on natural language requests. By continuously updating the tool, the system maintains reliability without requiring constant manual intervention from the developer.
5Performance and Efficiency Gains
Unlike traditional computer use which can be slow and prone to failure, Pomerado’s generated APIs typically return results within 5 to 30 seconds. While the initial setup requires a one-time exploration of the website, the subsequent runtime efficiency makes it ideal for high-volume, repetitive tasks that agents must perform consistently over time.
6Real-World Industry Applications
Early adopters include car dealerships connecting Grok Bots to legacy CRM and ERP systems, significantly reducing task times from over an hour to minutes. Additionally, personal trainers utilize the platform to automate client messaging and workout preparation. These use cases demonstrate the versatility of converting non-API sites into functional, automated agent workflows.
7Foundational Professional Experience
The founders bring experience from McKinsey and Scale AI, where they previously led agent deployments across healthcare, telecom, and professional services. Their background informed the design of Pomerado, specifically targeting the common failure points encountered when integrating AI agents with complex, non-standardized legacy web interfaces that lack modern developer-friendly API endpoints.
8Accessibility and Open Source
Pomerado is currently available through both an MIT-licensed open-source repository and a free hosted version. By offering these options, the team aims to lower the barrier for AI builders looking to integrate legacy verticals into their agentic workflows. Developers can begin creating their first MCP tools in under one hour.