Pomerado turns websites and legacy portals into deterministic APIs and MCP tools for AI agents with self-healing maintenance.
What the product does and how it is positioned
Pomerado is an open-source platform that converts consumer websites, legacy portals, and internal enterprise applications into deterministic API and Model Context Protocol endpoints. Instead of requiring browser agents to interpret and navigate web pages during every execution, it generates, tests, and deploys reusable tools that AI agents call directly.
The system handles full authentication workflows, including two-factor verification codes, and provides hosted execution environments that eliminate the need for custom infrastructure. It also includes automated maintenance routines that detect interface updates and patch failing workflow steps.
Source-supported ways to use the product
Connecting AI agents to healthcare provider portals and claims systems to inspect claim statuses, dates of service, and authorization outcomes without manual portal navigation.
Extracting vendor invoices, purchase orders, payment statuses, and dispute notes from legacy supplier portals directly into accounting and finance agent workflows.
Enabling personal assistants to search accommodations, compare airline fares, and inspect retail listings via deterministic HTTP and MCP queries.
The documented workflow, where available
Add the hosted MCP server configuration to your AI agent or coding assistant environment using the standard setup command.
Instruct your agent to search for an existing website tool or initiate the creation of a new one by specifying the target site, required parameters, and desired outputs.
Authenticate via the provided sign-in link or configure credentials and two-factor routing if the target site operates behind a login.
Pomerado maps the interface elements, handles form workflows, and runs both browser and HTTP test passes to validate returned data.
Run the published tool as a deterministic MCP or API call from your automated workflows, receiving structured data responses.
Web automation often fails when external platforms adjust form structures, shift navigation elements, or introduce updated search interfaces. Rather than surfacing unexpected errors to downstream agent workflows, Pomerado incorporates active monitoring that catches execution failures and triggers maintenance cycles.
When a failure occurs, the platform re-evaluates the target page layout, identifies the relocated elements or altered filter selectors, updates the execution logic, and validates the repair with fresh test passes before publishing the fix back to the live integration.
To maintain reliable communication with complex sites, Pomerado incorporates built-in rate limit management and anti-bot mitigation strategies, including the use of residential proxies, supporting consistent agent access across consumer and legacy web environments.
Checks to run with your own material and workflow
What was checked and when
Answers based on the source-checked product record
Yes. Integrations can authenticate into web portals, dashboards, and internal business tools to retrieve data and perform automated actions behind logins.
No. Users can supply credentials directly within each API request, though optional secure credential storage with two-factor support is also available.
The platform enforces native rate limits and handles anti-bot measures through techniques such as residential proxies to avoid blocking.
Execution results are removed once delivered to the caller, or deleted automatically within 60 minutes if the results remain unread.
Machine learning models are used to identify, redact, and remove personally identifiable information so sensitive details are not retained after a task finishes.
