Searches Tripadvisor locations and retrieves location details, reviews, and photos through MCP tools.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Tripadvisor MCP.
search_locationsSearch for locations by query text, category, and other filters
search_nearby_locationsFind locations near specific coordinates
get_location_detailsGet detailed information about a location
get_location_reviewsRetrieve reviews for a location
get_location_photosGet photos for a location
The pab1it0/tripadvisor-mcp MCP server exposes Tripadvisor Content API data through Model Context Protocol tools. It is intended for assistants that need to discover travel-related locations and retrieve supporting information such as descriptions, reviews, and photos.
Location searches can cover hotels, restaurants, and attractions. Search requests support query text, categories, and other filters. A separate nearby-search tool accepts geographic coordinates, which is useful for finding places around a known point rather than searching by name alone.
The server acts as an MCP interface over Tripadvisor’s API. An MCP client calls one of the available tools, and the server uses the configured Tripadvisor API key to request the corresponding data. Results are returned to the assistant through the standard MCP connection.
The pab1it0/tripadvisor-mcp MCP server can be run locally with the Python project’s uv workflow or inside Docker. The README demonstrates configuration for Claude Desktop. The available tool list is configurable, so a client can expose only the operations needed by an application.
A Tripadvisor Content API key is required. Obtain it through the Tripadvisor Developer Portal, then provide it in the TRIPADVISOR_API_KEY environment variable. The value can be placed in a .env file or supplied through the MCP client’s environment configuration.
For a local setup, the documented Claude Desktop configuration invokes uv against the project directory and runs src/tripadvisor_mcp/main.py. The project uses uv for dependency management and includes a pyproject.toml file. Docker users can build the included image as tripadvisor-mcp-server and pass the API key into the container with the same environment variable.
If Claude Desktop reports that it cannot find uv, the README suggests using the full path to the executable or setting NO_UV=1 in the client configuration. That setting is mentioned as a workaround for the launcher environment; the Tripadvisor key remains required.
The pab1it0/tripadvisor-mcp MCP server provides these tools:
search_locations: Search Tripadvisor locations using query text, categories, and other filters.search_nearby_locations: Find locations near supplied coordinates.get_location_details: Retrieve detailed data for a specific location.get_location_reviews: Retrieve reviews associated with a location.get_location_photos: Retrieve photos associated with a location.These operations support workflows such as discovering attractions near a destination, looking up a hotel or restaurant, and gathering reviews or images after identifying a location.
The server depends on the Tripadvisor Content API, so access requires a valid Tripadvisor API key. The provided material does not specify API quotas, response limits, supported API plan levels, or the exact response schema returned by each tool.
The README documents local execution and Docker deployment rather than a hosted endpoint. It also names Claude Desktop as an example client, but does not provide compatibility details for other MCP clients. Tool availability can be restricted through configuration, so clients may not expose every operation by default.
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