assess_trip

eu.mmatinca/travel-trends-mcp · Verify this server

Assess one trip: current disruption status for its destinations and dates. Use this tool when the user asks whether a specific trip is affected by strikes, weather, transport disruptions or other travel risks. Give the destinations and the travel window (date_from/date_to, YYYY-MM-DD). Destinations are the EU-27 ISO2 codes (Greece = "EL") PLUS the non-EU27 countries we actively monitor: Norway ("NO", rail via Entur, live), the United Kingdom ("UK" or "GB", transit via TfL, live), and Switzerland ("CH", rail via SBB — key-pending, so it is reported as a declared blind spot until the feed is keyed, never a false all-clear). A code we do not monitor is rejected with {"error": "unknown_country"} rather than silently all-cleared. Returns a Decision-Support answer, not raw data: * travel_status: NORMAL | MINOR_DISRUPTION | MAJOR_DISRUPTION; * actionable_lines: per-event DECISION-IMPACT guidance — what the disruption means for THIS trip and what to do (e.g. "affects regional trains, not airports -> take a road airport transfer, leave ~30 min earlier"), or a clearly-labelled "nothing material" line when calm; * confidence: a LABELLED model output (coverage/corroboration/recency/ blind-spots blend, not a probability) — read its caveats; * sources_checked: proof of what was monitored (sources_ok, blind spots); * events + caveats. Sub-floor noise (a deep, far-field seismic blip) is omitted; calm is a monitoring result for the window, never an invented forecast. Invalid inputs return an explicit {"error": ...}; nothing is fabricated. Top-level MCP-facing structure (additive; existing fields preserved): * presentation: a three-section block — affects_your_trip[] (each item with verified_sources[] as display-ready names, source_count, corroborated flag (≥2 distinct sources), an honest for_you line bound to destinations+dates only, report_url, first_detected_at, last_verified_at); doesnt_affect_your_trip (the proof-of-work pile — shown[] of {headline, reason_excluded}, additional_checked_count, summary_line, total_checked); next_steps[] (deterministic — re-check date, aviation-handoff watch when blind spot, per-active monitor URLs); * track_record_ref: lean {window_days, flagged, ended, still_active, monitoring_since, url} — numbers + URL only, no narrative; * suggested_next_call: {tool, context} — the suggested follow-up (watch_trip) when the user wants continued monitoring. These exist so an LLM consumer can quote verbatim — every fact is traceable to a named source or an input field, never invented. Destinations also accept natural input: IATA airport codes (e.g. 'TSR', 'AMS', 'ZRH') and major city names (e.g. 'Timișoara', 'Amsterdam', 'Zürich', 'London'), resolved deterministically to a monitored country code. The response includes a 'resolved' list ([{input, country, kind}]) disclosing how each token was mapped (e.g. 'TSR -> RO via iata-airport'). A token that resolves to a country we do not monitor is rejected with {'error': 'unknown_country'}; a token we cannot resolve at all is rejected with {'error': 'unknown_destination', 'tokens': [...]} — we reject rather than guess. Pass `lang` (e.g. "de", "ro", "pl", "fr", "es", "it"; default English) to answer in the traveller's language — useful for a traveller in a country whose language they do not speak. The response then carries a `localized` block with the status sentence, an honest reassurance line (calm ONLY when status is NORMAL), the decision-impact lines, AND — never dropped — the localized caveats + blind_spots. Source-derived free text the traveller cannot read (an event headline in the source language) is AI-translated via Gemini and carries the label "AI-translated — verify against the linked official source"; when no GEMINI_API_KEY is set or a translation fails, the original source text is kept with an honest note — never a fake translation. Our own wording falls back to English (flagged in `localized.fallback_lang_parts`) when no template exists for `lang`; an unknown `lang` answers in English and says so (`is_known_lang=false`). Localization NEVER becomes a false all-clear and the aviation handoff is a SIGNPOST that DISCLOSES the blind spot, not coverage. Pass `audience` for role-specific operational actions (B2B travel-risk / duty-of-care): one of "tmc" (travel management company / corporate travel risk), "hotel", "ota", "tour_operator". The response then carries a `persona` block: {audience, actions[]} where each action ties an affecting event to that role's recommended steps (e.g. TMC: flexible-rebooking policy, reroute inventory, proactive guest comms) — a PURE PROJECTION of the audience-tagged recommendations already computed per event, each carrying a `based_on` disclosure of the inputs it used. An unknown audience is reported honestly with the valid set, never guessed. Omit `audience` for the default (no persona block).