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Case Study № 001

JMPR Travel MCP

An AI-native Travel Model Context Protocol letting Claude and other agents plan real trips with provider data, structured outputs and natural conversation.

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<2min Avg. plan time
12+ Providers integrated
94% First-pass accuracy

Challenge

The travel industry is full of best-in-class APIs that never get used in the open. Most AI assistants planning trips today are flying blind guessing flight times, inventing hotel rates and hallucinating itineraries. The real signal live availability, real pricing, supplier rules lives behind walls.

The client needed a single MCP (Model Context Protocol) layer that any agent could plug into to access trusted travel data through a natural-language interface, while keeping each provider's commercial constraints intact.

Result

JMPR is the bridge. A production MCP server that handles search, availability, structured booking flows and the long-running orchestration agents need to actually finish a plan. Claude Sonnet on top, Trigger.dev underneath, and a typed schema for every provider.

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