# How to integrate Big data cloud MCP with LangChain

```json
{
  "title": "How to integrate Big data cloud MCP with LangChain",
  "toolkit": "Big data cloud",
  "toolkit_slug": "big_data_cloud",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/big_data_cloud/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/big_data_cloud/framework/langchain.md",
  "updated_at": "2026-05-12T10:03:00.370Z"
}
```

## Introduction

This guide walks you through connecting Big data cloud to LangChain using the Composio tool router. By the end, you'll have a working Big data cloud agent that can check if this ip address is currently roaming, verify if an email address is valid, get country and demographic info for a given ip through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Big data cloud account through Composio's Big data cloud MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Big data cloud with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Big data cloud project to Composio
- Create a Tool Router MCP session for Big data cloud
- Initialize an MCP client and retrieve Big data cloud tools
- Build a LangChain agent that can interact with Big data cloud
- 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 Big data cloud MCP server, and what's possible with it?

The Big data cloud MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Big data cloud account. It provides structured and secure access to advanced geolocation, reverse geocoding, ASN analysis, and data validation APIs, so your agent can perform actions like looking up IP details, verifying emails, assessing network risk, and analyzing BGP routing on your behalf.
- IP geolocation and country insights: Let your agent instantly geolocate any IP address, retrieve country-level demographics, and pull rich metadata about locations worldwide.
- Reverse geocoding with timezone detection: Have your agent translate GPS coordinates into precise locality information along with accurate timezone data—all in one go.
- Email address verification and data hygiene: Ensure your agent can validate email addresses for proper syntax, domain legitimacy, and disposability to help maintain clean and reliable datasets.
- ASN and BGP analytics: Allow your agent to analyze internet routing by fetching ranked lists of autonomous systems, upstream and downstream provider details, and active BGP prefixes for a given ASN.
- Cybersecurity hazard assessment: Empower your agent to fetch and interpret hazard reports for IP addresses, identifying threats like VPN/proxy usage, blacklist status, and hosting risks.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `BIG_DATA_CLOUD_AM_I_ROAMING_API` | Am I Roaming API | Tool to determine if the user is roaming based on their IP address and GPS coordinates. Use after obtaining device location to verify roaming status before mobile actions. |
| `BIG_DATA_CLOUD_ASN_EXTENDED_RECEIVING_FROM_INFO_API` | ASN Extended Receiving From Info API | Tool to return upstream providers (receivingFrom) for a given ASN. Use when you need a paginated list of ASes feeding traffic for the specified ASN. |
| `BIG_DATA_CLOUD_ASN_EXTENDED_TRANSIT_TO_INFO_API` | ASN Extended Transit To Info API | Tool to return downstream customers (transitTo) for a given ASN. Use when you need a paginated list of ASes receiving traffic from a specific ASN. |
| `BIG_DATA_CLOUD_ASN_RANK_LIST_API` | ASN Rank List API | Retrieves a ranked list of Autonomous Systems (ASNs) sorted by IPv4 address announcement volumes. Use cases: - Find the largest ASNs by IP address count (DoD, Amazon, Microsoft, etc.) - Look up ASN rankings for network analysis - Paginate through the global ASN database (79,000+ entries) - Sort ASNs by various criteria (rank, name, organisation, country) Returns paginated results with total count for navigation. |
| `BIG_DATA_CLOUD_BGP_ACTIVE_PREFIXES_API` | BGP Active Prefixes API | Tool to retrieve IPv4 or IPv6 prefixes currently announced on BGP. Use when inspecting BGP routing announcements for a given ASN. |
| `BIG_DATA_CLOUD_COUNTRY_BY_IP_ADDRESS_API` | Country by IP Address API | Tool to geolocate an IP address and retrieve country details and demographics. Use when you need country-level data after obtaining the target IP address. |
| `BIG_DATA_CLOUD_COUNTRY_INFO_API` | Country Info API | Tool to fetch detailed country information by ISO code. Use when you need localized names, currencies, regions, and other metadata for a country. |
| `BIG_DATA_CLOUD_EMAIL_ADDRESS_VERIFICATION_API` | Email Address Verification API | Tool to verify email addresses for syntax, domain validity, and disposability. Use after obtaining the email input. |
| `BIG_DATA_CLOUD_HAZARD_REPORT_API` | Hazard Report API | Tool to fetch a cybersecurity hazard report for a specified IP address. Use when assessing an IP's threat profile (VPN, proxy, blacklists, hosting risk). |
| `BIG_DATA_CLOUD_NETWORK_BY_CIDR` | Networks by CIDR | Tool to retrieve BGP-announced networks within a specified CIDR range. Use when you need to analyze network announcements within a particular CIDR after confirming the range format. |
| `BIG_DATA_CLOUD_NETWORK_BY_IP_ADDRESS_API` | Network by IP Address API | Tool to retrieve registry, ASN, and BGP details for a given IP address’s network. Use when you need detailed network information (e.g., ASNs, prefixes) after confirming the target IP. |
| `BIG_DATA_CLOUD_PHONE_NUMBER_VALIDATION_BY_IP` | Phone Number Validation by IP | Tool to validate phone numbers by inferring country from client IP. Use when you want to validate a number without specifying country. |
| `BIG_DATA_CLOUD_REVERSE_GEOCODING_TIMEZONE_API` | Reverse Geocoding With Timezone API | Tool to return reverse geocoding and time zone info for given coordinates. Use when you need both locality details and timezone data in one call. |
| `BIG_DATA_CLOUD_TIME_ZONE_BY_IP_ADDRESS_API` | Time Zone by IP Address API | Tool to retrieve time zone information for a given IP address. Use when you need DST status, UTC offsets, and local/UTC time for a specific IP. |
| `BIG_DATA_CLOUD_TOR_EXIT_NODES_GEOLOCATED_API` | Tor Exit Nodes Geolocated API | Retrieve a paginated list of active TOR exit node IP addresses with geolocation and carrier (ASN) details. Use this tool to: - Get a list of known TOR exit node IPs to detect/block anonymous traffic - Analyze geographic distribution of TOR exit nodes by country - Look up carrier/ASN information for TOR nodes - Build IP blocklists or allowlists for TOR traffic Returns nodes with IP address, country info (when available), and detailed carrier/ASN data including BGP prefix counts and global ranking. |
| `BIG_DATA_CLOUD_USER_AGENT_PARSER_API` | User Agent Parser API | Tool to parse a User-Agent string into device, OS, browser, and bot details. Use when you have a raw User-Agent header and need structured client info. |
| `BIG_DATA_CLOUD_USER_RISK_API` | User Risk API | Tool to return a risk assessment for a user based on IP signals for fraud prevention. Use after initial IP checks to decide whether to bypass or require captcha challenges. |

## Supported Triggers

None listed.

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

The Big data cloud MCP server is an implementation of the Model Context Protocol that connects your AI agent to Big data cloud. It provides structured and secure access so your agent can perform Big data cloud 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 Big data cloud 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 Big data cloud 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 Big data cloud tools as needed
```python
# Create Tool Router session for Big data cloud
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['big_data_cloud']
)

url = session.mcp.url
```

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

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

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

No description provided.
```python
client = MultiServerMCPClient({
    "big_data_cloud-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({
    "big_data_cloud-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 Big data cloud 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 Big data cloud 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=['big_data_cloud']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "big_data_cloud-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 Big data cloud 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: ['big_data_cloud']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "big_data_cloud-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 Big data cloud 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 Big data cloud 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 Big data cloud MCP Agent with another framework

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

## Related Toolkits

- [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management.
- [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters.
- [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agentql](https://composio.dev/toolkits/agentql) - Agentql is a toolkit that connects AI agents to the web using a specialized query language. It enables structured web interaction and data extraction for smarter automations.
- [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions.
- [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows.
- [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. Get detailed environmental insights directly from your own sensors for smarter apps and automations.
- [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements.
- [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints.
- [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots.
- [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches.
- [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand.
- [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance.
- [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses.
- [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research.
- [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction.
- [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation.
- [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation.
- [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Big data cloud MCP?

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

### Can I manage the permissions and scopes for Big data cloud while using Tool Router?

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

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