# How to integrate Bestbuy MCP with Autogen

```json
{
  "title": "How to integrate Bestbuy MCP with Autogen",
  "toolkit": "Bestbuy",
  "toolkit_slug": "bestbuy",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/bestbuy/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/bestbuy/framework/autogen.md",
  "updated_at": "2026-05-12T10:02:51.488Z"
}
```

## Introduction

This guide walks you through connecting Bestbuy to AutoGen using the Composio tool router. By the end, you'll have a working Bestbuy agent that can find top-rated laptops under $1000, list best buy stores near seattle, show reviews for samsung galaxy s24 through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Bestbuy account through Composio's Bestbuy MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Bestbuy with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the required dependencies for Autogen and Composio
- Initialize Composio and create a Tool Router session for Bestbuy
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Bestbuy tools
- Run a live chat loop where you ask the agent to perform Bestbuy operations

## What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.
Key features include:
- Multi-Agent Systems: Build collaborative agent workflows
- MCP Workbench: Native support for Model Context Protocol tools
- Streaming HTTP: Connect to external services through streamable HTTP
- AssistantAgent: Pre-built agent class for tool-using assistants

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

The Bestbuy MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Best Buy account. It provides structured and secure access to product, store, category, and review data, so your agent can perform actions like searching for products, retrieving store information, fetching detailed product specs, and analyzing customer reviews on your behalf.
- Browse and filter product listings: Instantly fetch Best Buy product catalogs, apply category filters, or sort by price and relevance to help users discover the right items.
- Retrieve detailed product information: Let your agent pull in-depth specifications, pricing, and availability for any product using its SKU, ensuring accurate recommendations or comparisons.
- Analyze and summarize customer reviews: Access and summarize customer feedback on products, or drill down into specific reviews to guide purchasing decisions.
- Explore store locations and details: Find Best Buy store locations near you, retrieve detailed store info, and assist with in-store shopping logistics or pickup arrangements.
- Navigate product categories and metadata: List, search, and explore Best Buy's extensive product categories, making it easy to organize options or narrow down shopping journeys.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `BESTBUY_GET_CATEGORIES` | Get Categories | Tool to retrieve Best Buy product categories. Use when you need to list or filter categories in the catalog. |
| `BESTBUY_GET_CATEGORY_DETAILS` | Get Category Details | Tool to retrieve detailed information about a Best Buy category by its ID. Use when you need enriched metadata about a specific category. |
| `BESTBUY_GET_PRODUCT_DETAILS` | Get Product Details by SKU | Tool to retrieve detailed information about a specific product by SKU. Use after obtaining a valid SKU to fetch its attributes. |
| `BESTBUY_GET_PRODUCTS` | Get Products | Tool to retrieve products from Best Buy. Use when you need to fetch product listings with optional filters and sorting. Example: 'Get products for category abcat0101000 sorted by salePrice.dsc.' |
| `BESTBUY_GET_REVIEW_DETAILS` | Get Review Details | Tool to retrieve detailed information for a specific review by ID. Use after confirming the review ID. |
| `BESTBUY_GET_REVIEWS` | Get Product Reviews | Tool to retrieve product reviews. Use when you need customer feedback with filters or sorting. Use after obtaining product SKUs. |
| `BESTBUY_GET_STORE_DETAILS` | Get Store Details | Tool to retrieve detailed information about a specific Best Buy store. Use when you have a valid store ID. |
| `BESTBUY_GET_STORES` | Get Best Buy Stores | Tool to retrieve a list of Best Buy stores. Use when you need store listings with optional filters or geo-search after confirming your API key. |

## Supported Triggers

None listed.

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

The Bestbuy MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Bestbuy. Instead of manually wiring Bestbuy APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
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

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Bestbuy account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 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).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

Install Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Bestbuy via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

Create a .env file in your project folder.
What's happening:
- COMPOSIO_API_KEY is required to talk to Composio
- OPENAI_API_KEY is used by Autogen's OpenAI client
- USER_ID is how Composio identifies which user's Bestbuy connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Bestbuy tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Bestbuy session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["bestbuy"]
    )
    url = session.mcp.url
```

### 5. Configure MCP parameters for Autogen

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.
What's happening:
- url points to the Tool Router MCP endpoint from Composio
- timeout is the HTTP timeout for requests
- sse_read_timeout controls how long to wait when streaming responses
- terminate_on_close=True cleans up the MCP server process when the workbench is closed
```python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Bestbuy tools from the workbench
```python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Bestbuy assistant agent with MCP tools
    agent = AssistantAgent(
        name="bestbuy_assistant",
        description="An AI assistant that helps with Bestbuy operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Bestbuy tools to call via MCP
- agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
- Typing exit, quit, or bye ends the loop
```python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Bestbuy related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Bestbuy session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["bestbuy"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Bestbuy assistant agent with MCP tools
        agent = AssistantAgent(
            name="bestbuy_assistant",
            description="An AI assistant that helps with Bestbuy operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Bestbuy related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

## Conclusion

You now have an Autogen assistant wired into Bestbuy through Composio's Tool Router and MCP. From here you can:
- Add more toolkits to the toolkits list, for example notion or hubspot
- Refine the agent description to point it at specific workflows
- Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Bestbuy, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Bestbuy MCP Agent with another framework

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

## Related Toolkits

- [Addresszen](https://composio.dev/toolkits/addresszen) - Addresszen is a real-time address autocomplete and verification service. It helps capture accurate, deliverable addresses with instant suggestions and validation.
- [Asin data api](https://composio.dev/toolkits/asin_data_api) - Asin data api gives you detailed, real-time product data from Amazon, including price, rank, and reviews. Perfect for e-commerce pros and data-driven marketers who need instant marketplace insights.
- [Baselinker](https://composio.dev/toolkits/baselinker) - BaseLinker is an all-in-one e-commerce management platform connecting stores, marketplaces, carriers, and more. It streamlines order processing, inventory control, and automates your sales operations.
- [Btcpay server](https://composio.dev/toolkits/btcpay_server) - BTCPay Server is a free, open-source, self-hosted Bitcoin payment processor. It lets merchants accept Bitcoin payments directly, cutting out middlemen and boosting privacy.
- [Cdr platform](https://composio.dev/toolkits/cdr_platform) - Cdr platform is an API for purchasing carbon dioxide removal services. It enables businesses to offset emissions by accessing verified carbon removal projects.
- [Cloudcart](https://composio.dev/toolkits/cloudcart) - CloudCart is an e-commerce platform for building and managing online stores. It helps businesses streamline product listings, orders, and customer engagement.
- [Countdown api](https://composio.dev/toolkits/countdown_api) - Countdown API gives you real-time, structured eBay product data, reviews, and seller feedback. Perfect for powering price monitoring, product research, or marketplace analytics workflows.
- [Dpd2](https://composio.dev/toolkits/dpd2) - Dpd2 is a robust email management platform for handling, sorting, and automating email workflows. Streamline your communications and boost productivity with advanced sorting, labeling, and response tools.
- [Finerworks](https://composio.dev/toolkits/finerworks) - FinerWorks is an online platform for fine art and photo printing services. Artists and photographers use it to order custom prints and manage print inventory efficiently.
- [Fingertip](https://composio.dev/toolkits/fingertip) - Fingertip is a business management platform for selling, booking, and customer engagement—all from a single link. It helps businesses streamline operations and connect with customers across social channels.
- [Fraudlabs pro](https://composio.dev/toolkits/fraudlabs_pro) - FraudLabs Pro is an online payment fraud detection service for e-commerce and merchants. It helps minimize chargebacks and revenue loss by detecting and preventing fraudulent transactions.
- [Gift up](https://composio.dev/toolkits/gift_up) - Gift Up! is a digital platform for selling, managing, and redeeming gift cards online. It streamlines promotions and gift card transactions for businesses and their customers.
- [Goody](https://composio.dev/toolkits/goody) - Goody is a gifting platform that lets users send gifts and physical products without handling logistics. It streamlines gifting by managing delivery, fulfillment, and recipient experience.
- [Gumroad](https://composio.dev/toolkits/gumroad) - Gumroad is a platform for selling digital products, physical goods, and memberships with a simple checkout and marketing tools. It streamlines creator payouts and helps you grow your audience effortlessly.
- [Instacart](https://composio.dev/toolkits/instacart) - Instacart is an online grocery delivery and pickup service platform. It lets you discover local retailers and create shoppable lists and recipes with ease.
- [Junglescout](https://composio.dev/toolkits/junglescout) - Junglescout is an Amazon product research and analytics platform for sellers. It delivers sales estimates, competitive insights, and optimization tools to boost your Amazon business.
- [Ko fi](https://composio.dev/toolkits/ko_fi) - Ko-fi is a platform that lets creators receive donations, memberships, and sales from fans. It helps creators monetize their work and grow their audience with minimal friction.
- [Lemon squeezy](https://composio.dev/toolkits/lemon_squeezy) - Lemon Squeezy is a payments and subscription platform built for software companies. It makes managing payments, taxes, and customer subscriptions effortless.
- [Loyverse](https://composio.dev/toolkits/loyverse) - Loyverse is a point-of-sale (POS) platform for small businesses, offering tools for sales, inventory, and customer loyalty. It helps streamline retail operations and boost customer engagement.
- [Memberstack](https://composio.dev/toolkits/memberstack) - Memberstack lets you add user authentication, payments, and member management to your website—no backend code required. Easily manage your site's members and subscriptions from a single platform.

## Frequently Asked Questions

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

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

### Can I use Tool Router MCP with Autogen?

Yes, you can. Autogen 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 Bestbuy tools.

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

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

---
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