The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Tripadvisor MCP listing page.
A Model Context Protocol (MCP) server for Tripadvisor Content API.
This provides access to Tripadvisor location data, reviews, and photos through standardized MCP interfaces, allowing AI assistants to search for travel destinations and experiences.
Search for locations (hotels, restaurants, attractions) on Tripadvisor
Get detailed information about specific locations
Retrieve reviews and photos for locations
Search for nearby locations based on coordinates
API Key authentication
Docker containerization support
Provide interactive tools for AI assistants
The list of tools is configurable, so you can choose which tools you want to make available to the MCP client.
Get your Tripadvisor Content API key from the Tripadvisor Developer Portal.
Configure the environment variables for your Tripadvisor Content API, either through a .env file or system environment variables:
Note: if you see
Error: spawn uv ENOENTin Claude Desktop, you may need to specify the full path touvor set the environment variableNO_UV=1in the configuration.
This project includes Docker support for easy deployment and isolation.
Build the Docker image using:
You can run the server using Docker in several ways:
Create a .env file with your Tripadvisor API key and then run:
To use the containerized server with Claude Desktop, update the configuration to use Docker with the environment variables:
This configuration passes the environment variables from Claude Desktop to the Docker container by using the -e flag with just the variable name, and providing the actual values in the env object.
Contributions are welcome! Please open an issue or submit a pull request if you have any suggestions or improvements.
This project uses uv to manage dependencies. Install uv following the instructions for your platform:
You can then create a virtual environment and install the dependencies with:
The project has been organized with a src directory structure:
The project includes a test suite that ensures functionality and helps prevent regressions.
Run the tests with pytest:
| Tool | Category | Description |
|---|---|---|
search_locations | Search | Search for locations by query text, category, and other filters |
search_nearby_locations | Search | Find locations near specific coordinates |
get_location_details | Retrieval | Get detailed information about a location |
get_location_reviews | Retrieval | Retrieve reviews for a location |
get_location_photos | Retrieval | Get photos for a location |
MIT