# How to integrate Bolt iot MCP with Autogen

```json
{
  "title": "How to integrate Bolt iot MCP with Autogen",
  "toolkit": "Bolt iot",
  "toolkit_slug": "bolt_iot",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/bolt_iot/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/bolt_iot/framework/autogen.md",
  "updated_at": "2026-05-12T10:03:32.053Z"
}
```

## Introduction

This guide walks you through connecting Bolt iot to AutoGen using the Composio tool router. By the end, you'll have a working Bolt iot agent that can read temperature sensor value from pin a0, turn on relay connected to digital pin 1, check if device bolt12345 is online now through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Bolt iot account through Composio's Bolt iot MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Bolt iot with

- [OpenAI Agents SDK](https://composio.dev/toolkits/bolt_iot/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/bolt_iot/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/bolt_iot/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/bolt_iot/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/bolt_iot/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/bolt_iot/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/bolt_iot/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/bolt_iot/framework/cli)
- [Google ADK](https://composio.dev/toolkits/bolt_iot/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/bolt_iot/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/bolt_iot/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/bolt_iot/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/bolt_iot/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/bolt_iot/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 Bolt iot
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Bolt iot tools
- Run a live chat loop where you ask the agent to perform Bolt iot 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 Bolt iot MCP server, and what's possible with it?

The Bolt iot MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bolt IoT account. It provides structured and secure access to your connected IoT devices, so your agent can perform actions like reading sensor values, controlling actuators, checking device status, and managing UART communication on your behalf.
- Real-time sensor data collection: Instantly retrieve analog sensor readings from any Bolt device for monitoring temperature, light, or other parameters.
- Remote device control: Command your agent to switch actuators, toggle LEDs, or send digital signals to devices using digital write operations.
- Device connectivity monitoring: Check if a specific Bolt IoT device is online before performing operations or troubleshooting connectivity issues automatically.
- Serial communication management: Read incoming serial data or transmit ASCII commands over UART to interact with other hardware modules connected to your Bolt device.
- Bidirectional UART automation: Send serial commands and immediately capture device responses in one seamless step, enabling complex automation workflows.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `BOLT_IOT_ANALOG_READ` | Analog Read | Tool to read the analog value from a specified pin on a Bolt device. Use when you need sensor readings (0–1023) after confirming the device is online. |
| `BOLT_IOT_CHECK_DEVICE_STATUS` | Check Bolt device online status | Tool to check whether a specified Bolt device is online. Use when you need to verify device connectivity before sending commands (e.g., control signals). Example: 'Check if device BOLT1234567 is online.' |
| `BOLT_IOT_DIGITAL_WRITE` | Bolt IoT Digital Write | Tool to set a digital pin HIGH or LOW on a specified Bolt device. Use when controlling actuators or LEDs via digital output. |
| `BOLT_IOT_SERIAL_READ` | Bolt IoT Serial Read | Tool to read incoming serial data from a Bolt device. Use when you've initialized UART with serialBegin and need to retrieve serial data. |
| `BOLT_IOT_SERIAL_WRITE` | Bolt IoT Serial Write | Tool to send serial data to a Bolt device. Use when you need to transmit ASCII data over UART after initializing UART with serialBegin. |
| `BOLT_IOT_SERIAL_WRITE_READ` | Bolt IoT Serial Write & Read | Tool to send serial data and read the response on a Bolt device. Use when you need to transmit ASCII data over UART and capture its reply immediately. |

## Supported Triggers

None listed.

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

The Bolt iot MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Bolt iot. Instead of manually wiring Bolt iot 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 Bolt iot 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 Bolt iot 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 Bolt iot 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 Bolt iot 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 Bolt iot session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["bolt_iot"]
    )
    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 Bolt iot 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 Bolt iot assistant agent with MCP tools
    agent = AssistantAgent(
        name="bolt_iot_assistant",
        description="An AI assistant that helps with Bolt iot 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 Bolt iot 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 Bolt iot 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 Bolt iot session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["bolt_iot"]
    )
    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 Bolt iot assistant agent with MCP tools
        agent = AssistantAgent(
            name="bolt_iot_assistant",
            description="An AI assistant that helps with Bolt iot 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 Bolt iot 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 Bolt iot 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 Bolt iot, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Bolt iot MCP Agent with another framework

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

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- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
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## Frequently Asked Questions

### What are the differences in Tool Router MCP and Bolt iot MCP?

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

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

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

---
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