How to integrate Emelia MCP with Mastra AI

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Introduction

This guide walks you through connecting Emelia to Mastra AI using the Composio tool router. By the end, you'll have a working Emelia agent that can find email address for john doe at acme corp, add jane.smith@email.com to new leads campaign, remove bob.jones@company.com from q2 outreach campaign, get recent activities from spring launch campaign through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Emelia account through Composio's Emelia 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 Emelia tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Emelia 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 Emelia 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 Emelia MCP server, and what's possible with it?

The Emelia MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Emelia account. It provides structured and secure access to your B2B outreach operations, so your agent can perform actions like launching campaigns, managing contacts, finding prospect emails, and tracking outreach activities on your behalf.

  • Automated campaign creation and management: Instruct your agent to create new email or LinkedIn campaigns, add contacts, or remove contacts from campaigns to keep your outreach efforts streamlined and organized.
  • Prospect email discovery: Have your agent find verified email addresses for specific contacts using full name and company details, accelerating your lead generation process.
  • Contact blacklisting and compliance: Direct your agent to add contacts to the blacklist, ensuring that no further emails are sent and helping you stay compliant with outreach best practices.
  • Real-time campaign activity tracking: Retrieve detailed campaign activities and create webhooks to monitor engagement, so you’re always up to date on your outreach performance.
  • Webhook automation for event-driven workflows: Let your agent create or delete webhooks to automate follow-ups and synchronize campaign updates across your sales stack.

Supported Tools & Triggers

Tools
Add Contact to BlacklistTool to add a contact to the email blacklist.
Add Contact To CampaignTool to add a contact to an email campaign.
Create CampaignTool to create a new email campaign.
Create LinkedIn CampaignTool to create a new linkedin campaign.
Create WebhookTool to create a new webhook for campaign events.
Delete Contact From CampaignTool to remove a contact from an email campaign.
Delete Contact From LinkedIn CampaignTool to delete a contact from a linkedin campaign.
Delete WebhookTool to delete a specific webhook.
Find Email of Single ContactTool to initiate a job to find the email address of a specific contact.
Get Campaign ActivitiesTool to retrieve activities for a specific email campaign.
Get Find Email ResultTool to retrieve the result of a previously initiated email find job.
Get Find Phone ResultTool to retrieve the outcome of a previously initiated phone-find job.
Get Verify Email ResultTool to get the result of an email verification job.
Initiate Email Verification JobTool to initiate an asynchronous email verification job.
Initiate Phone Find JobTool to initiate a phone-find job for a single contact.
List Campaign ContactsTool to list contacts in a specific email campaign.
List CampaignsTool to retrieve all email campaigns.
List Email ProvidersTool to retrieve all configured email providers.
List LinkedIn CampaignsTool to list all linkedin campaigns.
List webhooksTool to retrieve all webhooks.
Remove Contact from BlacklistTool to remove a contact or domain from the email blacklist.

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 Emelia 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 Emelia

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

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

Create the Mastra agent

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

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "emelia-mastra-agent",
    instructions: "You are an AI agent with Emelia 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: { emelia: 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 Emelia 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 Emelia MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Emelia MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Emelia MCP with Claude Agent SDK

Google ADK

Google ADK

Use Emelia MCP with Google ADK

LangChain

LangChain

Use Emelia MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Emelia MCP with Vercel AI SDK

LlamaIndex

LlamaIndex

Use Emelia MCP with LlamaIndex

CrewAI

CrewAI

Use Emelia MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Emelia MCP?

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

Can I manage the permissions and scopes for Emelia while using Tool Router?

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

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