# How to integrate Bolt iot MCP with LangChain

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

## Introduction

This guide walks you through connecting Bolt iot to LangChain 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 LangChain 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)
- [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
- Connect your Bolt iot project to Composio
- Create a Tool Router MCP session for Bolt iot
- Initialize an MCP client and retrieve Bolt iot tools
- Build a LangChain agent that can interact with Bolt iot
- Set up an interactive chat interface for testing

## What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.
Key features include:
- Agent Framework: Build agents that can use tools and make decisions
- MCP Integration: Connect to external services through Model Context Protocol adapters
- Memory Management: Maintain conversation history across interactions
- Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

## 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 agent to Bolt iot. It provides structured and secure access so your agent can perform Bolt iot 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

No description provided.

### 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

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters 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's API
- COMPOSIO_USER_ID identifies the user for session management
- OPENAI_API_KEY enables access to OpenAI's language models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
```

### 5. Initialize Composio client

What's happening:
- We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
- Creating a Composio instance that will manage our connection to Bolt iot tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Bolt iot tools
- The create method takes the user ID and specifies which toolkits should be available
- The returned session.mcp.url is the MCP server URL that your agent will use
- This approach allows the agent to dynamically load and use Bolt iot tools as needed
```python
# Create Tool Router session for Bolt iot
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['bolt_iot']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['bolt_iot']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "bolt_iot-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "bolt_iot-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

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")

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

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

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Bolt iot related question or task to the agent.\n");

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

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;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

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

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

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

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['bolt_iot']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "bolt_iot-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    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")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

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

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

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

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['bolt_iot']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "bolt_iot-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Bolt iot related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    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;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\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

You've successfully built a LangChain agent that can interact with Bolt iot through Composio's Tool Router.
Key features of this implementation:
- Dynamic tool loading through Composio's Tool Router
- Conversation history maintenance for context-aware responses
- Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

## 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)
- [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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- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
- [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data.

## 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 LangChain?

Yes, you can. LangChain 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.

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