How to integrate Extrovert MCP with Mastra AI

This guide walks you through connecting Extrovert to Mastra AI using the Composio tool router. By the end, you'll have a working Extrovert agent that can find linkedin prospects, list your campaigns, manage writing styles, manage contexts, and view plan features through natural language commands. This guide will help you understand how to give your Mastra AI agent real control over a Extrovert account through Composio's Extrovert MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Extrovert is a LinkedIn prospect engagement platform for campaigns, monitored topics, writing styles, contexts, and team workflows. It helps teams scale relevant outreach while keeping prospect conversations organized.

15 Tools

Introduction

This guide walks you through connecting Extrovert to Mastra AI using the Composio tool router. By the end, you'll have a working Extrovert agent that can find linkedin prospects, list your campaigns, manage writing styles, manage contexts, and view plan features through natural language commands.

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

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

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

The Extrovert MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Extrovert account. It provides structured and secure access to your campaigns, prospects, writing styles, engagement contexts, team, and workspace plan, so your agent can review campaigns, find prospects, manage messaging guidance, inspect team members, and check plan capabilities on your behalf.

  • Campaign monitoring: Have your agent list prospect and topic campaigns, then review their status, filters, automation settings, owners, and sharing configuration.
  • Prospect research: Let the agent browse prospects, inspect LinkedIn profile and engagement details, or check whether a LinkedIn profile already exists in your team's records.
  • Engagement context management: Direct your agent to create, review, update, or delete company and user background contexts used to guide prospect engagement.
  • Writing style management: Instruct your agent to create, review, update, or remove writing styles for LinkedIn comments and direct messages.
  • Team and plan visibility: Have your agent review visible team members and check your workspace plan, available features, API capabilities, and quota usage.

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 Extrovert 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 Extrovert

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

  const composioMCPUrl = session.mcp.url;
  console.log("Extrovert MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "extrovert" for Extrovert 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 Extrovert toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "extrovert-mastra-agent",
    instructions: "You are an AI agent with Extrovert 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: {
        extrovert: 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 Extrovert 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 Extrovert 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: ["extrovert"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "extrovert-mastra-agent",
    instructions: "You are an AI agent with Extrovert 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: { extrovert: 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 Extrovert 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 Extrovert action and event your agent gets out of the box.

Create Context

Create a Context for a user.

Create Style

Create a writing Style for a user.

Delete Context

Permanently delete one Context by UUID.

Delete Style

Permanently delete one Style by UUID.

Find Prospect by LinkedIn URL

Check whether a LinkedIn profile URL already exists among the team's prospects and return every matching prospect.

Get Campaign

Load full configuration and state for one campaign by its UUID.

Get Prospect

Load one existing prospect by UUID with LinkedIn profile, campaign and list bindings, flags, connection data, and engagement statistics.

Get Workspace Plan Features

Return the selected workspace's active plan, API capabilities, feature flags, and quota counters.

List Campaigns

Return all Prospects and Topic campaigns visible to the connected user, including their running state, owner, Context, Style, filters, automation, and sharing configuration.

List Contexts

Return all complete Context records owned by a user.

List Prospects

Return one page of existing prospects with campaign and list bindings, LinkedIn profile data, flags, connection state, and engagement statistics.

List Styles

Return all complete writing Styles owned by a user, including learning mode and separate comment and direct-message instructions.

List Team Members

Return users visible in the selected team, including the user IDs required to list or create owner-scoped contexts and styles.

Update Context

Fully replace a Context's name, company background, and user background.

Update Style

Update a Style's required name and learning-mode setting, optionally replacing or clearing its comment and DM instructions.

FRAMEWORKS

How to build Extrovert MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Extrovert MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Extrovert MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Extrovert MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Extrovert MCP with Claude Cowork

Codex logo

Codex

Use Extrovert MCP with Codex

OpenClaw logo

OpenClaw

Use Extrovert MCP with OpenClaw

Hermes logo

Hermes

Use Extrovert MCP with Hermes

CLI logo

CLI

Use Extrovert MCP with CLI

Google ADK logo

Google ADK

Use Extrovert MCP with Google ADK

LangChain logo

LangChain

Use Extrovert MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Extrovert MCP with Vercel AI SDK

LlamaIndex logo

LlamaIndex

Use Extrovert MCP with LlamaIndex

CrewAI logo

CrewAI

Use Extrovert MCP with CrewAI

FAQ

Frequently asked questions

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

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

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