"Travel" matching MCP servers:

Enables travel-related queries and planning including weather, train and flight information, itinerary generation, and travel knowledge retrieval via RAG, using an AI agent with MCP protocol.

Search 70,000+ cruise voyages, 678 ships, and 62 cruise lines worldwide. No API key needed, no installation required — just paste the URL. Includes RAG-powered knowledge search for ship dining, facilities, cabins, and port guides. 30 languages supported.

Enables users to plan Singapore itineraries by combining a retrieval-augmented knowledge base with live weather forecasts and currency conversion through MCP tools.

MCP server for Lakehouse42, enabling code-first tool discovery, hybrid search, document management, and Iceberg time-travel queries with optimized responses.

Enables persistent storage and retrieval of Tree of Thought search states in PostgreSQL, allowing the travel agent to maintain reasoning context across multi-turn itinerary optimization.

Provides AI agents an auditable memory layer with provable deletion via signed certificates, a tamper-evident hash-chained audit trail, and bi-temporal time-travel recall over SQLite or Postgres.

Enables MCP clients to search encrypted, self-hosted archives and retrieve bounded records from Apple, Canvas, Health, travel, and Obsidian sources while checking sync freshness.

Local-first memory for Claude & AI agents with hybrid search, Graph-RAG, and time-travel, runs entirely on your machine.

Enables LLM assistants to store, retrieve, and update user-specific context memory including travel preferences and general information through a chat interface. Provides analytics on tool usage patterns and token costs for continuous improvement.

Gives AI agents persistent memory with bi-temporal tracking, automatically extracting entities from natural language and enabling time-travel queries to understand facts as they existed at any point in history.

Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.

Enables coding agents to search an approved local repository root for code and document evidence, returning source paths and line spans without source editing or network access.

Enables AI agents to store and recall durable facts, decisions, and lessons over MCP using hybrid semantic and keyword search, typed memories, graph relations, sessions, and time-travel queries. Runs locally with no server process or API key, persisting everything to files that both agents and a CLI can share.

Enables AI agents to run an AI-driven text interactive fiction engine by initializing a worldview from a setting, resolving player actions through academic combat, trade, social and karma models, pulling narration context, advancing turns, and tracking emergent events across million-turn campaigns with tiered memory and summaries. Also imports SillyTavern character cards and world-info lorebooks, travel and codex tracking, snapshots, and serves a read-only live status panel.

Exposes twelve annotated tools over stdio JSON-RPC that let an MCP client search an HR policy corpus and query mock employee records, PTO, benefits, travel history, and ticketing data. This enables grounded, citation-backed answers to HR policy and operations questions that require combining written rules with a specific employee's data.

Enables analysis of documents far larger than an LLM's context window by letting the model issue constrained symbolic commands that execute server-side against in-memory handles, so only compact result stubs—rather than raw text—travel through the conversation. It also provides server-side memo storage with expandable handles, letting agents retain and retrieve large context across long sessions at a fraction of the token cost.