How to integrate Seat geek MCP with CrewAI

Framework Integration Gradient
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Introduction

This guide walks you through connecting Seat geek to CrewAI using the Composio tool router. By the end, you'll have a working Seat geek agent that can find concerts happening in new york this weekend, show me available seats for taylor swift’s next show, recommend sports events near san francisco next month, list upcoming comedy shows at madison square garden through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Seat geek account through Composio's Seat geek MCP server.

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

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Seat geek connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Seat geek
  • Build a conversational loop where your agent can execute Seat geek operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

What is the Seat geek MCP server, and what's possible with it?

The Seat geek MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to SeatGeek's event and ticketing platform. It provides structured and secure access to real-time event listings, performer info, venues, and recommendations—so your agent can search events, fetch performer or venue details, get personalized recommendations, and explore seating options on your behalf.

  • Event discovery and search: Instantly search for concerts, sports games, theater shows, and more by performer, venue, location, or date to find upcoming live entertainment that matches your preferences.
  • Venue and seating insights: Retrieve detailed information about venues, including seating charts and available sections or rows, so your agent can help you choose the best seats for any event.
  • Performer exploration and recommendations: Get in-depth details about your favorite artists, teams, or entertainers, and discover similar performers or new acts you might enjoy based on your interests.
  • Personalized event recommendations: Ask your agent to suggest events tailored to your tastes, location, or favorite performers, making it easy to find something you'll love.
  • Event category browsing: Explore a rich taxonomy of event types, from concerts and sports to theater and comedy, enabling your agent to filter and recommend experiences across all entertainment genres.

Supported Tools & Triggers

Tools
Get Event DetailsGet comprehensive details about a specific event including venue, performers, date/time, and ticket information.
Get Event RecommendationsGet personalized event recommendations based on your favorite performers, events, or location.
Get Event Seating InformationGet detailed section and row information for an event to understand the venue layout and available seating options.
Get Performer DetailsGet detailed information about a specific performer including images, scores, and related metadata.
Get Performer RecommendationsGet recommendations for similar performers based on your interests.
Get Event CategoriesGet a list of all available event categories and types (taxonomies) used on seatgeek.
Get Venue DetailsGet detailed information about a specific venue including location, address, and other metadata.
Search EventsSearch for events on seatgeek by performers, venues, dates, or general queries.
Search PerformersSearch for performers including artists, bands, sports teams, comedians, and more.
Search VenuesSearch for venues by location, name, or other criteria.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Seat geek connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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.

Install dependencies

bash
pip install composio crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Seat geek via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Seat geek MCP URL

Create a Composio Tool Router session for Seat geek

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["seat_geek"],
)
url = session.mcp.url
What's happening:
  • You create a Seat geek only session through Composio
  • Composio returns an MCP HTTP URL that exposes Seat geek tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Seat geek Assistant",
    goal="Help users interact with Seat geek through natural language commands",
    backstory=(
        "You are an expert assistant with access to Seat geek tools. "
        "You can perform various Seat geek operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Seat geek MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Seat geek operations.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Seat geek related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_seat_geek_agent.py

Complete Code

Here's the complete code to get you started with Seat geek and CrewAI:

python
# file: crewai_seat_geek_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

def main():
    # Initialize Composio and create a Seat geek session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["seat_geek"],
    )
    url = session.mcp.url

    # Configure LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Seat geek assistant agent
    toolkit_agent = Agent(
        role="Seat geek Assistant",
        goal="Help users interact with Seat geek through natural language commands",
        backstory=(
            "You are an expert assistant with access to Seat geek tools. "
            "You can perform various Seat geek operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Seat geek operations.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Seat geek related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Seat geek through Composio's Tool Router. The agent can perform Seat geek operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Seat geek MCP Agent with another framework

FAQ

What are the differences in Tool Router MCP and Seat geek MCP?

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

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI 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 Seat geek tools.

Can I manage the permissions and scopes for Seat geek while using Tool Router?

Yes, absolutely. You can configure which Seat geek 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.

How safe is my data with Composio Tool Router?

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 Seat geek data and credentials are handled as safely as possible.

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