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How to integrate Tripadvisor content api MCP with Autogen

Connect Autogen to Tripadvisor content api MCP. Find top-rated restaurants in rome, show recent photos of eiffel tower, and more using natural language, with authentication handled for you.

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Api Key

Tripadvisor content api provides access to Tripadvisor’s massive travel database, including 7.5M+ locations and 1B+ reviews. Instantly enrich your app with trusted, global travel content from a single source.

5 Tools

Introduction

This guide walks you through connecting Tripadvisor content api to AutoGen using the Composio tool router. By the end, you'll have a working Tripadvisor content api agent that can search locations, find nearby places, fetch location details, read reviews, and browse photos through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Tripadvisor content api account through Composio's Tripadvisor content api MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Tripadvisor content api with

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TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Tripadvisor content api
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Tripadvisor content api tools
  • Run a live chat loop where you ask the agent to perform Tripadvisor content api operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

What is the Tripadvisor content api MCP server, and what's possible with it?

The Tripadvisor content api MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Tripadvisor content api account. It provides structured and secure access to Tripadvisor’s massive travel data, so your agent can search destinations, retrieve location details, and fetch high-quality photos from the world’s largest travel platform on your behalf.

  • Location search and discovery: Instantly have your agent find detailed information on hotels, attractions, restaurants, and more by name or keyword.
  • Photo retrieval for destinations: Fetch recent, high-quality images for any Tripadvisor location to enhance travel recommendations or trip planning experiences.
  • Multi-language data access: Access content and reviews in up to 29 languages, making it easy to build global-ready applications and assistants.
  • Trip planning assistance: Enable your agent to suggest popular spots, review ratings, and gather visual inspiration for any itinerary or travel question.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Tripadvisor content api account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Tripadvisor content api via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Tripadvisor content api connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Tripadvisor content api session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["tripadvisor_content_api"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Tripadvisor content api tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Tripadvisor content api assistant agent with MCP tools
    agent = AssistantAgent(
        name="tripadvisor_content_api_assistant",
        description="An AI assistant that helps with Tripadvisor content api operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Tripadvisor content api tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Tripadvisor content api related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Tripadvisor content api tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Tripadvisor content api and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Tripadvisor content api session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["tripadvisor_content_api"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Tripadvisor content api assistant agent with MCP tools
        agent = AssistantAgent(
            name="tripadvisor_content_api_assistant",
            description="An AI assistant that helps with Tripadvisor content api operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Tripadvisor content api related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You now have an Autogen assistant wired into Tripadvisor content api through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Tripadvisor content api, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Tripadvisor content api action and event your agent gets out of the box.

Get Location Details

Tool to get comprehensive information about a location (hotel, restaurant, or attraction) including name, address, rating, and contact details.

Get Location Photos (Enhanced)

Tool to retrieve up to 5 high-quality photos for a specific location with complete metadata and pagination support.

Get Location Reviews

Tool to retrieve up to 5 of the most recent reviews for a specific location.

Search Locations (Advanced)

Search for Tripadvisor locations by name, with optional filters for category, phone, address, coordinates, and radius.

Search Nearby Locations

Tool to search for locations near a specified latitude/longitude.

FRAMEWORKS

How to build Tripadvisor content api MCP Agent with another framework

Claude Code logo

Claude Code

Use Tripadvisor content api MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Tripadvisor content api MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Tripadvisor content api MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Tripadvisor content api MCP with Claude Agent SDK

Codex logo

Codex

Use Tripadvisor content api MCP with Codex

OpenClaw logo

OpenClaw

Use Tripadvisor content api MCP with OpenClaw

Hermes logo

Hermes

Use Tripadvisor content api MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Tripadvisor content api MCP with Atomic Agent

Google ADK logo

Google ADK

Use Tripadvisor content api MCP with Google ADK

LangChain logo

LangChain

Use Tripadvisor content api MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Tripadvisor content api MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Tripadvisor content api MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Tripadvisor content api MCP with LlamaIndex

CrewAI logo

CrewAI

Use Tripadvisor content api MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Tripadvisor content api MCP with Pydantic AI

FAQ

Frequently asked questions

With a standalone Tripadvisor content api MCP server, the agents and LLMs can only access a fixed set of Tripadvisor content api tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Tripadvisor content api and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Autogen fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Tripadvisor content api tools.

Yes, absolutely. You can configure which Tripadvisor content api scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Tripadvisor content api data and credentials are handled as safely as possible.

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