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Tripadvisor Mcp
What is Tripadvisor Mcp
tripadvisor-mcp is a Model Context Protocol (MCP) server designed for the Tripadvisor Content API. It provides standardized access to Tripadvisor location data, reviews, and photos, enabling AI assistants to search for travel destinations and experiences.
Use cases
Use cases include developing travel planning applications, enhancing AI assistants with travel recommendations, and integrating Tripadvisor data into websites or mobile apps for user engagement.
How to use
To use tripadvisor-mcp, obtain a Tripadvisor Content API key from the Tripadvisor Developer Portal. Configure the necessary environment variables and add the server configuration to your client configuration file. Optionally, you can deploy it using Docker for easier management.
Key features
Key features include searching for locations (hotels, restaurants, attractions), retrieving detailed information, accessing reviews and photos, searching for nearby locations based on coordinates, API Key authentication, and Docker containerization support.
Where to use
tripadvisor-mcp can be used in travel-related applications, AI assistants, and any platform that requires access to Tripadvisor’s extensive location data and user-generated content.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Tripadvisor Mcp
tripadvisor-mcp is a Model Context Protocol (MCP) server designed for the Tripadvisor Content API. It provides standardized access to Tripadvisor location data, reviews, and photos, enabling AI assistants to search for travel destinations and experiences.
Use cases
Use cases include developing travel planning applications, enhancing AI assistants with travel recommendations, and integrating Tripadvisor data into websites or mobile apps for user engagement.
How to use
To use tripadvisor-mcp, obtain a Tripadvisor Content API key from the Tripadvisor Developer Portal. Configure the necessary environment variables and add the server configuration to your client configuration file. Optionally, you can deploy it using Docker for easier management.
Key features
Key features include searching for locations (hotels, restaurants, attractions), retrieving detailed information, accessing reviews and photos, searching for nearby locations based on coordinates, API Key authentication, and Docker containerization support.
Where to use
tripadvisor-mcp can be used in travel-related applications, AI assistants, and any platform that requires access to Tripadvisor’s extensive location data and user-generated content.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Tripadvisor MCP Server
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.
Features
-
[x] Search for locations (hotels, restaurants, attractions) on Tripadvisor
-
[x] Get detailed information about specific locations
-
[x] Retrieve reviews and photos for locations
-
[x] Search for nearby locations based on coordinates
-
[x] API Key authentication
-
[x] Docker containerization support
-
[x] 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.
Usage
-
Get your Tripadvisor Content API key from the Tripadvisor Developer Portal.
-
Configure the environment variables for your Tripadvisor Content API, either through a
.envfile or system environment variables:
# Required: Tripadvisor Content API configuration TRIPADVISOR_API_KEY=your_api_key_here
- Add the server configuration to your client configuration file. For example, for Claude Desktop:
{
"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 ENOENTin Claude Desktop, you may need to specify the full path touvor set the environment variableNO_UV=1in the configuration.
Docker Usage
This project includes Docker support for easy deployment and isolation.
Building the Docker Image
Build the Docker image using:
docker build -t tripadvisor-mcp-server .
Running with Docker
You can run the server using Docker in several ways:
Using docker run directly:
docker run -it --rm \
-e TRIPADVISOR_API_KEY=your_api_key_here \
tripadvisor-mcp-server
Using docker-compose:
Create a .env file with your Tripadvisor API key and then run:
docker-compose up
Running with Docker in Claude Desktop
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.
Development
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 .
Project Structure
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
Testing
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
Tools
| 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 |
License
MIT
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










