Switching AI tools shouldn't mean reintroducing your API
Every new coding assistant starts with the same ritual: paste the docs, explain the fields, warn about stale versions. A local spec served over MCP makes that context permanent.
Every new coding assistant starts with the same ritual: paste the docs, explain the fields, warn about stale versions. A local spec served over MCP makes that context permanent.
AI across the entire API lifecycle, drafting operations from cURL or Postman, generating tests, explaining failures, with a review-and-revert model and a local-first guarantee: your file stays the source of truth.
A booking app built from one prompt can pass every visual check and still fail on time zones, double bookings, and stale cancel responses. Teams need a contract both people and tools can query, change, and verify.
A request that runs is the start of a handoff, not the end of one. Import the curl, capture the missing context, and promote what you learned back into the specification.
Real systems are multi-protocol: REST at the edge, WebSockets for events, gRPC between services, GraphQL at the gateway. Powerduck debugs all of them from the same workspace and the same spec.
The field changed in code, in chat, and in the HTTP client while the docs waited for someone to care. A local OpenAPI file in version control gives the whole team one contract to diff, review, and trust.
Postman collections, mock servers, docs generators and MCP glue all drift the moment the spec stops being the source of truth. Powerduck keeps one local OpenAPI file at the center.