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How to integrate Yelp MCP with Mastra AI

Connect Mastra AI to Yelp MCP. Find top-rated coffee shops nearby, show best pizza places open now, and more using natural language, with authentication handled for you.

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Yelp is a local business directory and review platform with millions of listings. Instantly access rich business data, ratings, and customer reviews for location-based services.

12 Tools

Introduction

This guide walks you through connecting Yelp to Mastra AI using the Composio tool router. By the end, you'll have a working Yelp agent that can search businesses, read reviews and highlights, get business details, find events, and look up businesses by phone through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Yelp account through Composio's Yelp MCP server.

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

Also integrate Yelp with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKLlamaIndexCrewAIPydantic AIAutoGen

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

The Yelp MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, and more directly to Yelp's extensive business data. It provides structured and secure access to business search, reviews, ratings, and local business details, so your agent can help you find businesses, compare ratings, read reviews, and discover local favorites on your behalf.

  • Business discovery and search: Ask your agent to find restaurants, shops, or services by location, category, or specific business name with up-to-date Yelp data.
  • Detailed review retrieval: Have your agent fetch and summarize customer reviews for any business, making it easier to choose where to go.
  • Ratings and reputation checks: Let your agent provide business ratings, number of reviews, and popularity insights before you make a decision.
  • Local business information access: Get detailed information like address, hours, contact info, and amenities for businesses near you or in any city.
  • Personalized recommendations: Enable your agent to suggest top-rated options based on your preferences, trending spots, or special occasions.

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 step09 STEPS
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
2

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 Yelp through MCP.
3

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
4

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
5

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
6

Create a Tool Router session for Yelp

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

  const composioMCPUrl = session.mcp.url;
  console.log("Yelp MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "yelp" for Yelp access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

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 Yelp toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "yelp-mastra-agent",
    instructions: "You are an AI agent with Yelp 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
9

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: {
        yelp: 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 Yelp 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 Yelp 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: ["yelp"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "yelp-mastra-agent",
    instructions: "You are an AI agent with Yelp 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: { yelp: 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 Yelp 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
TOOLS

Supported Tools

Every Yelp action and event your agent gets out of the box.

Autocomplete Search

Get autocomplete suggestions for businesses, categories, and search terms on Yelp based on partial text input.

Get Business Details

Get detailed information about a Yelp business by ID or alias, including location, photos, rating, review count and, when available, hours and phone number.

Get Business Reviews

Get reviews for a specific business on Yelp using its business ID or alias.

Get Category Details

Get detailed information about a specific Yelp category by its alias.

Get Event Details

Get details of a Yelp event by its event ID, including dates, location, cost, attendance counts and, when available, the associated business ID.

Get Featured Event

Get the featured event for a given location on Yelp.

Get Review Highlights

Get review highlights for a specific business on Yelp using its business ID or alias.

List Categories

List all Yelp business categories across all locales by default.

Search and Chat

Chat with Yelp's AI assistant to search for businesses, get recommendations, and ask questions.

Search Businesses

Search Yelp businesses by location, term, categories and other filters, with up to 50 results per call and offset pagination.

Search Business by Phone

Search for a business by phone number on Yelp.

Search Events

Search for events on Yelp by location, categories, and other filters.

FRAMEWORKS

How to build Yelp MCP Agent with another framework

Claude Code logo

Claude Code

Use Yelp MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Yelp MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Yelp MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Yelp MCP with Claude Agent SDK

Codex logo

Codex

Use Yelp MCP with Codex

OpenClaw logo

OpenClaw

Use Yelp MCP with OpenClaw

Hermes logo

Hermes

Use Yelp MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Yelp MCP with Atomic Agent

Google ADK logo

Google ADK

Use Yelp MCP with Google ADK

LangChain logo

LangChain

Use Yelp MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Yelp MCP with Vercel AI SDK

LlamaIndex logo

LlamaIndex

Use Yelp MCP with LlamaIndex

CrewAI logo

CrewAI

Use Yelp MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Yelp MCP with Pydantic AI

AutoGen logo

AutoGen

Use Yelp MCP with AutoGen

FAQ

Frequently asked questions

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

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 Yelp tools.

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

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