How to integrate Phantombuster MCP with Mastra AI

This guide walks you through connecting Phantombuster to Mastra AI using the Composio tool router. By the end, you'll have a working Phantombuster agent that can download agent usage csv for last month, list all active agents in your account, get the country for this ip address through natural language commands. This guide will help you understand how to give your Mastra AI agent real control over a Phantombuster account through Composio's Phantombuster MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Get started for freeGet a demo
Phantombuster logoPhantombuster
Api Key

Phantombuster is a cloud-based automation platform for extracting web data and automating actions online. It helps you automate lead generation, web scraping, and social media workflows at scale.

53 Tools

Introduction

This guide walks you through connecting Phantombuster to Mastra AI using the Composio tool router. By the end, you'll have a working Phantombuster agent that can download agent usage csv for last month, list all active agents in your account, get the country for this ip address through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Phantombuster account through Composio's Phantombuster MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Phantombuster with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKLlamaIndexCrewAI

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 Phantombuster tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Phantombuster 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 Phantombuster 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 Phantombuster MCP server, and what's possible with it?

The Phantombuster MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Phantombuster account. It provides structured and secure access to your web automation and data extraction tools, so your agent can perform actions like running agents, fetching reports, exporting usage data, and managing your automations on your behalf.

  • Agent management and monitoring: Instantly list, audit, or fetch details about all your Phantombuster agents and see which are active, deleted, or grouped together.
  • Data extraction and export: Have your agent export detailed usage reports or download CSVs of agent and container activity for analytics and compliance.
  • Automation workflow insight: Get visibility into branches, containers, and deployment differences—helping you track automation changes and resource usage.
  • Organization and account overview: Let your agent retrieve comprehensive organization information or check current API key associations for security and collaboration.
  • IP geolocation support: Enable your agent to look up the physical location of specific IP addresses for auditing or compliance checks.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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

Step by step09 STEPS
1

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
2

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 Phantombuster through MCP.
3

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
4

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
5

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
6

Create a Tool Router session for Phantombuster

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

  const composioMCPUrl = session.mcp.url;
  console.log("Phantombuster MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "phantombuster" for Phantombuster access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

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 Phantombuster toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "phantombuster-mastra-agent",
    instructions: "You are an AI agent with Phantombuster 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
9

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: {
        phantombuster: 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 Phantombuster 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 Phantombuster 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: ["phantombuster"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "phantombuster-mastra-agent",
    instructions: "You are an AI agent with Phantombuster 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: { phantombuster: 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 Phantombuster 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
TOOLS

Supported Tools

Every Phantombuster action and event your agent gets out of the box.

Abort Agent (v1)

Tool to abort all running instances of an agent using the legacy v1 API.

Delete Agent

Tool to delete an agent by id.

Delete Lead Objects

Tool to delete one or more lead objects from organization storage.

Delete Many Leads

Tool to delete multiple leads from organization storage.

Delete List

Tool to delete a storage list by id (Beta).

Delete Script

Tool to delete a script by id.

Get Agent

Tool to get an agent by its ID.

Get Agent Containers (v1)

Tool to get a list of ended containers for an agent, ordered by date.

Get Agent Output (v1)

Tool to get incremental data from an agent including console output, status, progress and messages.

Get All Agents

Tool to fetch all agents associated with the current user or organization.

Get Deleted Agents

Tool to get deleted agents for the current user or organization.

Get Branches Diff

Tool to get the length difference between the staging and release branch of all scripts.

Get All Branches

Tool to fetch all branches associated with the current organization.

Get Containers Fetch All

Tool to get all containers associated with a specified agent.

Get Leads By List

Tool to fetch leads by their list ID.

Get IP Location

Tool to retrieve the country of a given or environment IP address.

Export Agent Usage CSV

Tool to export agent usage CSV for current organization.

Export Container Usage CSV

Tool to export container usage CSV for current organization.

Get Organization

Tool to fetch current organization details.

Get Agent Groups

Tool to get agent groups and order for the current organization.

Get Organization Resources

Tool to get current organization's resources and usage.

Get Org Running Containers

Tool to get the current organization's running containers.

Get Org Storage Lists Fetch All

Tool to fetch all storage lists for the authenticated organization.

Get Script

Tool to fetch a script by its unique ID.

Get Script by Name

Tool to retrieve a script by its name from Phantombuster (Legacy v1 API).

Get Script Code

Tool to get the code of a script.

Get All Scripts

Tool to fetch all scripts for the current user.

Get User Information

Tool to get information about your PhantomBuster account and your agents using the legacy v1 API.

Unschedule All Agent Launches

Tool to unschedule all scheduled launches for agents.

Request AI Completion

Tool to request a text completion from the AI module.

Create Branch

Tool to create a new branch.

Delete Branch

Tool to delete a branch by id.

Solve hCaptcha

Tool to solve an hCaptcha challenge.

Generate Identity Token

Tool to generate an identity token for PhantomBuster.

Save Many Leads

Tool to save multiple leads (1-20) to organization storage in a single batch operation (Beta).

Solve reCAPTCHA

Tool to solve a reCAPTCHA challenge (v2 or v3).

Update Script Visibility

Tool to update the visibility of a script.

Release Branch

Tool to release a script branch.

Save Agent

Tool to create a new agent or update an existing one.

Save Agent Groups

Tool to update agent groups and order for the current user's organization.

Save Company Object

Tool to save one company object to the organization storage.

Save Many Company Objects

Tool to save many company objects to organization storage.

Save Identity Event

Tool to save an identity event to Phantombuster.

Save Lead

Tool to save or update a lead in Phantombuster org storage.

Save Lead Object

Tool to save a lead object to organization storage.

Save Many Lead Objects

Tool to save multiple lead objects to Phantombuster's organization storage.

Save List

Tool to save (create or update) a list with filter criteria.

Save Script

Tool to create a new script or update an existing one.

Search Company Objects

Tool to search company objects in Phantombuster's organizational storage.

Search Lead Objects

Tool to search lead objects in Phantombuster org storage.

Stop Agent

Tool to stop a running agent.

Update Script (v1 API)

Tool to update an existing script or create a new one if it does not exist (Legacy v1 API).

Update Script Access List

Tool to update the access list of a script.

FRAMEWORKS

How to build Phantombuster MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Phantombuster MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Phantombuster MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Phantombuster MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Phantombuster MCP with Claude Cowork

Codex logo

Codex

Use Phantombuster MCP with Codex

OpenClaw logo

OpenClaw

Use Phantombuster MCP with OpenClaw

Hermes logo

Hermes

Use Phantombuster MCP with Hermes

CLI logo

CLI

Use Phantombuster MCP with CLI

Google ADK logo

Google ADK

Use Phantombuster MCP with Google ADK

LangChain logo

LangChain

Use Phantombuster MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Phantombuster MCP with Vercel AI SDK

LlamaIndex logo

LlamaIndex

Use Phantombuster MCP with LlamaIndex

CrewAI logo

CrewAI

Use Phantombuster MCP with CrewAI

FAQ

Frequently asked questions

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

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 Phantombuster tools.

Yes, absolutely. You can configure which Phantombuster 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.

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 Phantombuster data and credentials are handled as safely as possible.

Start with Phantombuster.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Phantombuster tool your agent needs.Free to start.

Start building
Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREEBOOK A DEMO
agent.aiZoomLettaGleanHubSpotAWSWabi

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche
Jerome Leclanche
Co-Founder, Ingram Technologies