How to integrate Radar MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Radar to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Radar agent that can autocomplete address based on partial input, get users currently inside geofence, convert address to latitude and longitude, retrieve detailed info for a specific trip through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Radar account through Composio's Radar 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 and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Radar
  • Configure an AI agent that can use Radar as a tool
  • Run a live chat session where you can ask the agent to perform Radar operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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

The Radar MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Radar account. It provides structured and secure access to advanced location services, so your agent can perform actions like geocoding addresses, managing geofences, tracking trips, searching places, and retrieving location context on your behalf.

  • Address and place autocomplete: Instantly get relevant address or place suggestions based on partial user input, improving data quality and user experience.
  • Precise geocoding and location context: Convert full addresses to latitude/longitude and fetch rich context—including region, geofence, and place details—for any set of coordinates.
  • Geofence management: Retrieve, create, or delete geofences to define dynamic boundaries and monitor activity within specific areas automatically.
  • Trip creation and tracking: Start, fetch, or delete trips to enable real-time location tracking and trip management for devices or users.
  • Live user monitoring in geofences: Effortlessly list all users currently inside a defined geofence, supporting presence-based automation and analytics.

Supported Tools & Triggers

Tools
Autocomplete Address or PlaceTool to autocomplete partial addresses and place names based on relevance and proximity.
Create TripTool to create a new trip.
Delete GeofenceTool to delete a geofence by id.
Delete TripTool to delete a trip by its radar id or external id.
Forward GeocodeTool to convert an address into geographic coordinates.
Get Context for LocationTool to retrieve context for a given location.
Get GeofenceTool to retrieve a geofence by radar id or tag/externalid.
Get Places SettingsTool to retrieve current places settings for your radar project.
Get TripTool to retrieve a trip by id or externalid.
Get Users in GeofenceTool to retrieve users currently within a specific geofence.
IP GeocodeTool to geocode an ip address to city, state, and country.
List BeaconsTool to list all beacons sorted by creation date.
List EventsTool to list events.
List GeofencesTool to list all geofences sorted by updated time.
List TripsTool to list all trips, sorted by updated time.
List UsersTool to list radar users sorted by update time.
Reverse GeocodeTool to convert geographic coordinates to structured addresses.
Route DistanceTool to compute distance and travel time between origins and destinations.
Search GeofencesTool to search for geofences near a given location.
Search Places Near LocationTool to search for places near given coordinates.
Search Users Near LocationTool to search for users near a location.
Track Location UpdateTool to track a user's location update.
Update TripTool to update a trip.
Upsert GeofenceTool to create or update a geofence by tag and externalid.

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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Radar project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Radar.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Radar Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["radar"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only radar.
  • The router checks the user's Radar connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Radar.
  • This approach keeps things lightweight and lets the agent request Radar tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Radar. "
        "Help users perform Radar operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Radar and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Radar operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Radar.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Radar and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["radar"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Radar. "
        "Help users perform Radar operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Radar MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Radar.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Radar MCP Agent with another framework

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Mastra AI

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CrewAI

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Use Radar MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Radar MCP?

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

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Radar tools.

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

Yes, absolutely. You can configure which Radar 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 Radar data and credentials are handled as safely as possible.

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