# How to integrate Foursquare MCP with Mastra AI

```json
{
  "title": "How to integrate Foursquare MCP with Mastra AI",
  "toolkit": "Foursquare",
  "toolkit_slug": "foursquare",
  "framework": "Mastra AI",
  "framework_slug": "mastra-ai",
  "url": "https://composio.dev/toolkits/foursquare/framework/mastra-ai",
  "markdown_url": "https://composio.dev/toolkits/foursquare/framework/mastra-ai.md",
  "updated_at": "2026-05-12T10:12:14.885Z"
}
```

## Introduction

This guide walks you through connecting Foursquare to Mastra AI using the Composio tool router. By the end, you'll have a working Foursquare agent that can find coffee shops open near me now, show photos of central park attractions, get reviews for the best pizza spots nearby through natural language commands.
This guide will help you understand how to give your Mastra AI agent real control over a Foursquare account through Composio's Foursquare MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Foursquare with

- [OpenAI Agents SDK](https://composio.dev/toolkits/foursquare/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/foursquare/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/foursquare/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/foursquare/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/foursquare/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/foursquare/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/foursquare/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/foursquare/framework/cli)
- [Google ADK](https://composio.dev/toolkits/foursquare/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/foursquare/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/foursquare/framework/ai-sdk)
- [LlamaIndex](https://composio.dev/toolkits/foursquare/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/foursquare/framework/crew-ai)

## 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 Foursquare tools
- Connect Mastra's MCP client to the Composio generated MCP URL
- Fetch Foursquare 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 Foursquare 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 Foursquare MCP server, and what's possible with it?

The Foursquare MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Foursquare account. It provides structured and secure access to the powerful Foursquare Places database, so your agent can search for venues, recommend places, retrieve detailed location data, surface user tips, and even fetch photos—all on your behalf.
- Comprehensive place search and discovery: Let your agent find places or points of interest nearby or in any area using keywords, categories, or specific criteria.
- Retrieve rich place details: Instantly pull in-depth information about a specific venue, including its name, address, ratings, categories, and more.
- Access user-generated tips and reviews: Have your agent surface real user insights, tips, and experiences for any place to help guide your decisions.
- Fetch location photos: Enhance your applications by retrieving and displaying user-contributed images for any venue in the Foursquare database.
- Explore lesser-known and trending spots: Use Foursquare's broader search to discover new, up-and-coming, or hidden places that might not appear in standard searches.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `FOURSQUARE_RETRIEVE_NEARBY_PLACES_V3` | Retrieve nearby places v3 | The GetNearbyPlaces endpoint retrieves a list of places near a specified location, primarily supporting check-in use cases and local discovery. It returns points of interest (POIs) including lower quality results not found in the standard Place Search, enhancing location-based experiences with additional data like photos, reviews, and tips. This endpoint is ideal for applications seeking to provide users with a comprehensive view of their surroundings, including less prominent or newer locations. While it offers a broader range of results, it may sacrifice some precision compared to more focused search endpoints. Use this when you want to offer users a diverse array of nearby options, particularly for social check-in features or exploratory local recommendations. |
| `FOURSQUARE_RETRIEVE_PLACE_PHOTOS_BY_ID` | Retrieve place photos by id | Retrieves photos associated with a specific place in Foursquare's database. This endpoint allows you to access user-generated images for a particular point of interest (POI) using its unique Foursquare ID (fsq_id). It's useful for enhancing your application with visual content related to locations, such as restaurants, landmarks, or businesses. The endpoint returns photo data that can be used to construct image URLs for display. Keep in mind that the number and quality of photos may vary depending on the popularity and user engagement of the place. This tool should be used when you need to display or analyze visual information about a specific location in your application. |
| `FOURSQUARE_RETRIEVE_PLACES_BY_ID` | Retrieve places by id | Retrieves detailed information about a specific place using its unique Foursquare ID (FSQ ID). This endpoint provides comprehensive data about a venue, including its name, address, category, ratings, tips, photos, and other relevant information. It's particularly useful when you need in-depth details about a known location, such as for displaying venue profiles or gathering specific place attributes. The endpoint should be used when you have a valid FSQ ID and require the most up-to-date and complete information about that place. Note that this endpoint focuses on individual place details and does not provide search functionality or lists of multiple venues. |
| `FOURSQUARE_RETRIEVE_PLACE_TIPS_USING_FSQ_ID` | Retrieve place tips using fsq id | Retrieves user-generated tips for a specific place in the Foursquare database. This endpoint allows you to fetch valuable insights and experiences shared by Foursquare users about a particular venue. It's useful for enhancing location-based applications with real user feedback, helping users make informed decisions about places they might visit. The endpoint returns a list of tips, which may include information such as the tip text, the user who created it, and potentially a timestamp or rating. |
| `FOURSQUARE_SEARCH_PLACES_API_REQUEST` | Search places api request | The GetPlacesSearch endpoint allows you to search for places in the Foursquare database based on various criteria such as location, keywords, and categories. This tool is ideal for discovering nearby points of interest or finding specific venues. It returns a list of places matching the specified parameters, providing essential information about each location. Use this endpoint for location-based features or gathering venue information in a specific area. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Foursquare MCP server is an implementation of the Model Context Protocol that connects your AI agent to Foursquare. It provides structured and secure access so your agent can perform Foursquare operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. 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

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.
- This key lets your Mastra agent talk to Composio and reach Foursquare through MCP.

### 2. Install dependencies

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

### 3. Set up environment variables

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
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import libraries and validate environment

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
```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,
});
```

### 5. Create a Tool Router session for Foursquare

What's happening:
- create spins up a short-lived MCP HTTP endpoint for this user
- The toolkits array contains "foursquare" for Foursquare access
- session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
```typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["foursquare"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Foursquare MCP URL:", composioMCPUrl);
```

### 6. Configure Mastra MCP client and fetch tools

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 Foursquare toolkit
```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);
```

### 7. Create the Mastra agent

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

### 8. Set up interactive chat interface

What's happening:
- messages keeps the full conversation history in Mastra's expected format
- agent.generate runs the agent with conversation history and Foursquare 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
```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: {
        foursquare: 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);
});
```

## Complete Code

```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: ["foursquare"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "foursquare-mastra-agent",
    instructions: "You are an AI agent with Foursquare 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: { foursquare: 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 Foursquare 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 Foursquare MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/foursquare/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/foursquare/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/foursquare/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/foursquare/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/foursquare/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/foursquare/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/foursquare/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/foursquare/framework/cli)
- [Google ADK](https://composio.dev/toolkits/foursquare/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/foursquare/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/foursquare/framework/ai-sdk)
- [LlamaIndex](https://composio.dev/toolkits/foursquare/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/foursquare/framework/crew-ai)

## Related Toolkits

- [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management.
- [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters.
- [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions.
- [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows.
- [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. Get detailed environmental insights directly from your own sensors for smarter apps and automations.
- [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements.
- [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints.
- [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots.
- [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches.
- [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand.
- [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance.
- [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows.
- [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses.
- [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research.
- [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction.
- [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation.
- [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation.
- [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Foursquare MCP?

With a standalone Foursquare MCP server, the agents and LLMs can only access a fixed set of Foursquare tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Foursquare 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 Foursquare tools.

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

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)