# How to integrate Yelp MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Yelp MCP with OpenAI Agents SDK",
  "toolkit": "Yelp",
  "toolkit_slug": "yelp",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/yelp/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/yelp/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:30:54.821Z"
}
```

## Introduction

This guide walks you through connecting Yelp to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Yelp agent that can find top-rated coffee shops nearby, show best pizza places open now, list vegan restaurants within 2 miles through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK 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 Agent SDK](https://composio.dev/toolkits/yelp/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/yelp/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/yelp/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/yelp/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/yelp/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/yelp/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/yelp/framework/cli)
- [Google ADK](https://composio.dev/toolkits/yelp/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/yelp/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/yelp/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/yelp/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/yelp/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/yelp/framework/crew-ai)

## 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 Yelp
- Configure an AI agent that can use Yelp as a tool
- Run a live chat session where you can ask the agent to perform Yelp operations

## What is OpenAI 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 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.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `YELP_GET_BUSINESS_DETAILS` | Get Business Details | Get detailed information about a specific business on Yelp using its business ID or alias. Returns comprehensive business information including hours (in the business's local timezone), photos, reviews, and location details. The returned `url` field is the Yelp listing page, not the business's own website. Response fields such as `phone` and `website` may be null; handle missing values explicitly. Avoid many parallel calls — HTTP 429 throttling applies; limit concurrency to ~5 parallel requests with exponential backoff. |
| `YELP_GET_BUSINESS_REVIEWS` | Get Business Reviews | Get reviews for a specific business on Yelp using its business ID or alias. Returns up to 3 review excerpts for the business. |
| `YELP_GET_REVIEW_HIGHLIGHTS` | Get Review Highlights | Get review highlights for a specific business on Yelp using its business ID or alias. Returns summarized key points and themes from customer reviews. IMPORTANT: This endpoint requires Yelp Places API Premium Plan access. Without Premium Plan, requests will return a 403 NOT_AUTHORIZED error. For basic review access, consider using the Get Business Reviews action instead, which is available on Enhanced and Premium plans. Note: Get Business Reviews returns at most 3 recent reviews per call, while this action synthesizes themes across the full review history. |
| `YELP_SEARCH_AND_CHAT` | Search and Chat | Chat with Yelp's AI assistant to search for businesses, get recommendations, and ask questions. This action provides a conversational interface to Yelp's AI that can: - Search for businesses by type, location, and criteria (e.g., "best Italian restaurants near Times Square") - Answer questions about specific businesses (e.g., "what are the hours for The Purple Pig?") - Provide recommendations based on user preferences - Maintain conversation context when chat_id is provided for follow-up questions The response includes the AI's natural language answer along with detailed business data including ratings, reviews, locations, photos, and attributes for any mentioned businesses. |
| `YELP_SEARCH_BUSINESSES` | Search Businesses | Search for businesses on Yelp by location, term, categories, and other filters. Returns at most 50 results per call; use offset to paginate. Overly restrictive filter combinations (categories, price, radius) can yield zero results — loosen iteratively. Results may include businesses from adjacent areas; post-process on location.city or distance for strict boundaries. The returned url field is the Yelp listing page, not the business's own website. Rapid parallel calls can trigger HTTP 429 — apply exponential backoff. |
| `YELP_SEARCH_BY_PHONE` | Search Business by Phone | Search for a business by phone number on Yelp. Returns business data including business_id, required by YELP_GET_BUSINESS_DETAILS, YELP_GET_BUSINESS_REVIEWS, and YELP_GET_REVIEW_HIGHLIGHTS. Empty results are inconclusive due to incomplete Yelp coverage. |

## Supported Triggers

None listed.

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

The Yelp MCP server is an implementation of the Model Context Protocol that connects your AI agent to Yelp. It provides structured and secure access so your agent can perform Yelp 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:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live Yelp project
- Some knowledge of Python or 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'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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

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 Yelp.
```python
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
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
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())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only yelp.
- The router checks the user's Yelp connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Yelp.
- This approach keeps things lightweight and lets the agent request Yelp tools only when needed during the conversation.
```python
# Create a Yelp Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["yelp"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Yelp
const session = await composio.create(userId as string, {
  toolkits: ['yelp'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Yelp. "
        "Help users perform Yelp 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",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Yelp. Help users perform Yelp operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
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())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

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

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
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=["yelp"]
)
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 Yelp. "
        "Help users perform Yelp 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())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['yelp'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Yelp. Help users perform Yelp operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

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

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});
```

## Conclusion

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

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

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## Frequently Asked Questions

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

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.

### 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 Yelp tools.

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

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.

### 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 Yelp data and credentials are handled as safely as possible.

---
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