How to integrate Radar MCP with Mastra AI

Trusted by
AWS
Glean
Zoom
Airtable
GET STARTED FOR FREEGET A DEMO

30 min · no commitment · see it on your stack

Radar logo
Mastra AI logo
divider

Introduction

This guide walks you through connecting Radar to Mastra AI 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 through natural language commands.

This guide will help you understand how to give your Mastra AI 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.

Also integrate Radar with

TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Radar tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Radar tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Radar agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

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 BeaconTool to create a new beacon in Radar.
Create TripTool to create a new trip.
Delete BeaconTool to delete a beacon by its Radar ID.
Delete GeofenceTool to delete a geofence by ID.
Delete Geofence By TagTool to delete a geofence by tag and external ID.
Delete TripTool to delete a trip by its Radar ID or external ID.
Delete UserTool to delete a user by Radar _id, userId, or deviceId.
Forward GeocodeTool to convert an address into geographic coordinates.
Get BeaconTool to retrieve a beacon by Radar _id.
Get Beacon By TagTool to get a specific beacon by tag and external ID.
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 Route DirectionsTool to get turn-by-turn directions between multiple locations.
Get Route MatrixTool to calculate travel distance and duration between multiple origins and destinations for up to 625 routes.
Get TripTool to retrieve a trip by ID or externalId.
Get UserTool to get a user by Radar _id, userId, or deviceId.
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 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 Places SettingsTool to update Places settings for your Radar project including chain metadata preferences.
Update TripTool to update a trip.
Update Trip By IDTool to update a trip status by Radar _id or external ID.
Upsert Beacon by IDTool to create or update a beacon by Radar _id.
Upsert Beacon by TagTool to create or update a beacon by tag and externalId.
Upsert GeofenceTool to create or update a geofence by tag and externalId.
Upsert Geofence By IDTool to create or update a geofence by Radar _id.

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

Prerequisites

Before starting, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Radar through MCP.

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_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 your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session

Create a Tool Router session for Radar

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["radar"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Radar MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "radar" for Radar access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Radar toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "radar-mastra-agent",
    instructions: "You are an AI agent with Radar tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        radar: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Radar toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Radar and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["radar"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      radar: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "radar-mastra-agent",
    instructions: "You are an AI agent with Radar tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { radar: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Radar through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows

How to build Radar MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Radar MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Radar MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Radar MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Radar MCP with Claude Cowork

Codex logo

Codex

Use Radar MCP with Codex

OpenClaw logo

OpenClaw

Use Radar MCP with OpenClaw

Hermes logo

Hermes

Use Radar MCP with Hermes

CLI logo

CLI

Use Radar MCP with CLI

Google ADK logo

Google ADK

Use Radar MCP with Google ADK

LangChain logo

LangChain

Use Radar MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Radar MCP with Vercel AI SDK

LlamaIndex logo

LlamaIndex

Use Radar MCP with LlamaIndex

CrewAI logo

CrewAI

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 Mastra AI?

Yes, you can. Mastra AI 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.

Used by agents from

Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Get started for freeGet a demo↗