How to integrate Big data cloud MCP with Mastra AI

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Introduction

This guide walks you through connecting Big data cloud to Mastra AI 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, fetch cybersecurity hazard report for this ip through natural language commands.

This guide will help you understand how to give your Mastra AI 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.

TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Big data cloud tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Big data cloud tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Big data cloud agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

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 & Triggers

Tools
Am I Roaming APITool to determine if the user is roaming based on their ip address and gps coordinates.
ASN Extended Receiving From Info APITool to return upstream providers (receivingfrom) for a given asn.
ASN Extended Transit To Info APITool to return downstream customers (transitto) for a given asn.
ASN Rank List APITool to fetch a ranked list of autonomous systems by ipv4 announcement volumes.
BGP Active Prefixes APITool to retrieve ipv4 or ipv6 prefixes currently announced on bgp.
Reverse Geocoding With Timezone APITool to return reverse geocoding and time zone info for given coordinates.
Country by IP Address APITool to geolocate an ip address and retrieve country details and demographics.
Country Info APITool to fetch detailed country information by iso code.
Email Address Verification APITool to verify email addresses for syntax, domain validity, and disposability.
Hazard Report APITool to fetch a cybersecurity hazard report for a specified ip address.
Networks by CIDRTool to retrieve bgp-announced networks within a specified cidr range.
Network by IP Address APITool to retrieve registry, asn, and bgp details for a given ip address’s network.
Phone Number Validation by IPTool to validate phone numbers by inferring country from client ip.
Time Zone by IP Address APITool to retrieve time zone information for a given ip address.
Tor Exit Nodes Geolocated APITool to list active tor exit nodes geolocated by country with carrier info.
User Agent Parser APITool to parse a user-agent string into device, os, browser, and bot details.
User Risk APITool to return a risk assessment for a user based on ip signals for fraud prevention.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Big data cloud through MCP.

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session

Create a Tool Router session for Big data cloud

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["big_data_cloud"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Big data cloud MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "big_data_cloud" for Big data cloud access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Big data cloud toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "big_data_cloud-mastra-agent",
    instructions: "You are an AI agent with Big data cloud tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

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

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;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        big_data_cloud: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Big data cloud toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Big data cloud and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["big_data_cloud"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      big_data_cloud: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "big_data_cloud-mastra-agent",
    instructions: "You are an AI agent with Big data cloud tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

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

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { big_data_cloud: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Big data cloud through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows

How to build Big data cloud MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Big data cloud MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Big data cloud MCP with Claude Agent SDK

Google ADK

Google ADK

Use Big data cloud MCP with Google ADK

LangChain

LangChain

Use Big data cloud MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Big data cloud MCP with Vercel AI SDK

LlamaIndex

LlamaIndex

Use Big data cloud MCP with LlamaIndex

CrewAI

CrewAI

Use Big data cloud MCP with CrewAI

FAQ

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 Mastra AI?

Yes, you can. Mastra AI 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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