Purpose: tripadvisor-mcp is a Model Context Protocol (MCP) server for the Tripadvisor Content API. Through a standardized MCP interface, it enables AI assistants to access Tripadvisor location data, reviews, and photos, so they can search for travel destinations and experiences.
Main capabilities: supports searching for places on Tripadvisor (hotels, restaurants, attractions); retrieving detailed information about a specific place; retrieving reviews and photos of a place; searching for nearby places based on coordinates; supports API Key authentication; supports Docker containerized deployment; provides interactive tools to AI assistants. The tool list is configurable, and users can choose which tools to expose to the MCP client.
Usage: a Tripadvisor Content API key is required from the Tripadvisor Developer Portal. Configure the Tripadvisor Content API environment variables through a .env file or system environment variables. Add the server configuration to the client configuration file (for example, Claude Desktop). If you encounter Error: spawn uv ENOENT in Claude Desktop, you may need to specify the full path to uv, or set the environment variable NO_UV=1 in the configuration. The project supports Docker, and you can build an image and run the server in multiple ways; when using a containerized server in Claude Desktop, you can update the configuration to run with Docker plus environment variables, passing only the variable names via the -e flag and providing the actual values in the env object. The project uses uv to manage dependencies; install uv according to the platform-specific instructions, then create a virtual environment and install dependencies. The project uses a src directory structure, includes a test suite, and tests can be run with pytest.
Use cases: suitable for application scenarios that require an AI assistant to query travel destinations, hotels, restaurants, attraction information, reviews, and photos, as well as to find nearby places based on coordinates.
Limitations: the material does not provide specific environment variable names, complete configuration examples, detailed Docker build and run commands, a complete list of supported tools, API call limits or quotas, pricing information, and so on; these details are not yet provided.
