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.
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:
# Required: Tripadvisor Content API configuration
TRIPADVISOR_API_KEY=your_api_key_here
{
"mcpServers": {
"tripadvisor": {
"command": "uv",
"args": [
"--directory",
"<full path to tripadvisor-mcp directory>",
"run",
"src/tripadvisor_mcp/main.py"
],
"env": {
"TRIPADVISOR_API_KEY": "your_api_key_here"
}
}
}
}
Note: if you see
Error: spawn uv ENOENT
in Claude Desktop, you may need to specify the full path touv
or set the environment variableNO_UV=1
in the configuration.
This project includes Docker support for easy deployment and isolation.
Build the Docker image using:
docker build -t tripadvisor-mcp-server .
You can run the server using Docker in several ways:
docker run -it --rm \
-e TRIPADVISOR_API_KEY=your_api_key_here \
tripadvisor-mcp-server
Create a .env
file with your Tripadvisor API key and then run:
docker-compose up
To use the containerized server with Claude Desktop, update the configuration to use Docker with the environment variables:
{
"mcpServers": {
"tripadvisor": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-e", "TRIPADVISOR_API_KEY",
"tripadvisor-mcp-server"
],
"env": {
"TRIPADVISOR_API_KEY": "your_api_key_here"
}
}
}
}
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:
curl -LsSf https://astral.sh/uv/install.sh | sh
You can then create a virtual environment and install the dependencies with:
uv venv
source .venv/bin/activate # On Unix/macOS
.venv\Scripts\activate # On Windows
uv pip install -e .
The project has been organized with a src
directory structure:
tripadvisor-mcp/
├── src/
│ └── tripadvisor_mcp/
│ ├── __init__.py # Package initialization
│ ├── server.py # MCP server implementation
│ ├── main.py # Main application logic
├── Dockerfile # Docker configuration
├── docker-compose.yml # Docker Compose configuration
├── .dockerignore # Docker ignore file
├── pyproject.toml # Project configuration
└── README.md # This file
The project includes a test suite that ensures functionality and helps prevent regressions.
Run the tests with pytest:
# Install development dependencies
uv pip install -e ".[dev]"
# Run the tests
pytest
# Run with coverage report
pytest --cov=src --cov-report=term-missing
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