Polarsteps MCP Server

The Polarsteps MCP server bridges the gap between travel enthusiasts and AI assistants by exposing a rich set of travel data through an easy‑to‑use protocol. It taps into Polarsteps’ user profiles, itineraries, and analytics via an undocumented API wrapper, allowing Claude or any MCP‑compatible assistant to retrieve personalized travel information with a simple natural‑language prompt. This eliminates the need for developers to build custom scrapers or handle OAuth flows, enabling instant access to travel histories and statistics that would otherwise require manual export.

At its core, the server offers four main capabilities. First, User Profiles return basic account details and social metrics such as followers or travel streaks. Second, Trip Data provides comprehensive itineraries—dates, locations, and photos—so an assistant can describe a journey in vivid detail. Third, Smart Search allows fuzzy matching on destinations or themes, enabling queries like “find all trips to Japan” without needing exact identifiers. Finally, Travel Analytics aggregates global statistics—countries visited, days traveled, and milestones achieved—giving users a quick overview of their travel footprint. These features are exposed through straightforward JSON endpoints that the MCP client can invoke, making it trivial to integrate into existing conversational flows.

Developers will appreciate how the server integrates seamlessly with AI workflows. Once configured, a user can ask Claude questions such as “Show me my travel stats” or “What country should I add to my bucket list?” The assistant translates the request into an MCP call, receives structured data, and formats it in natural language—all without additional coding. This tight coupling between the AI’s intent understanding and the Polarsteps data layer reduces latency, keeps context consistent, and eliminates repetitive authentication steps.

Real‑world scenarios span from personal travel planning to analytics dashboards. A solo traveler can query past trips to generate packing lists or compare destinations, while a travel agency could surface client itineraries for personalized recommendations. Even marketing teams can use aggregated analytics to identify popular destinations among a user base. Because the server relies on an existing token stored in an environment variable, it requires minimal setup and adheres to Polarsteps’ terms of use with a clear legal disclaimer.

Overall, the Polarsteps MCP server delivers a unique advantage: it unlocks private travel data for AI assistants without exposing credentials or violating API boundaries. By providing a concise, well‑documented interface, it empowers developers to create richer, data‑driven conversational experiences that feel both natural and deeply personalized.