How to Use the TripAdvisor MCP in Google ADK

Q: Can I get detailed reports on a place using TripAdvisor and Google ADK?

Yes. After finding a location via searchlocation, the agent pulls full details with getlocationdetails. You can then export that comprehensive record into your enterprise data lake.

Q: What happens when I need to check surrounding areas using TripAdvisor and Google ADK?

The agent calls getnearbylocations with a coordinate pair. It returns all relevant POIs in that immediate area, which you can then process alongside your existing regional data.

Q: Does TripAdvisor support multiple types of searches with Google ADK?

It does. The searchlocation tool handles hotels, restaurants, and attractions using a single input mechanism (name or address).

Connect enterprise BigQuery data with TripAdvisor insights using Google ADK.

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Connect TripAdvisor MCP to Google ADK

Create your Vinkius account to connect TripAdvisor to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup TripAdvisor with Google ADK

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Search and Gather POI Data

Start the process by calling `search_location` within your agent workflow. This tool lets you query for hotels, restaurants, or attractions simply by name or address. Once a match is found, the agent can proceed to get detailed info using `get_location_details`. This makes it easy to ingest structured location data and feed it directly into BigQuery tables for later analysis.

Process User Reviews at Scale

You can run `get_location_reviews` to pull user feedback. Because of the long context window in Gemini, your agent can analyze hundreds of reviews and categorize them automatically—say, grouping complaints about 'parking' vs. 'staff.' This is better than simple keyword matching; it understands the nuance of what people are actually saying.

Find Localized Points of Interest

Use `get_nearby_locations` when you need a radius search. Give the agent coordinates, and it returns all POIs nearby. Your enterprise system can then cross-reference these results against existing data in Vertex AI. It’s ideal for building operational dashboards that require real-time geographical awareness.

Setup guide

Set up TripAdvisor MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with TripAdvisor tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="TripAdvisor_agent",
    model="gemini-2.0-flash",
    instruction="You have access to TripAdvisor tools via MCP.",
    tools=mcp_tools,
)

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Common questions about TripAdvisor MCP in Google ADK

The MCP Server exposes several tools your agent can use. Your AI client, running on Google Cloud, discovers these methods and lets you build workflows that integrate external data into BigQuery.

Yes. After finding a location via `search_location`, the agent pulls full details with `get_location_details`. You can then export that comprehensive record into your enterprise data lake.

The agent calls `get_nearby_locations` with a coordinate pair. It returns all relevant POIs in that immediate area, which you can then process alongside your existing regional data.

It does. The `search_location` tool handles hotels, restaurants, and attractions using a single input mechanism (name or address).

The primary data type handled is Location IDs. These identifiers are crucial for linking the external POI data back to your internal records in BigQuery.

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