How to integrate Intercom MCP with Mastra AI

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Introduction

This guide walks you through connecting Intercom to Mastra AI using the Composio tool router. By the end, you'll have a working Intercom agent that can add tag 'vip' to contact john doe, assign open conversation #123 to support team, create note for contact emily about refund, close all resolved conversations from today through natural language commands.

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

The Intercom MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Intercom account. It provides structured and secure access to your customer engagement platform, so your agent can perform actions like managing conversations, tagging contacts, creating articles, and updating company records on your behalf.

  • Conversation management and assignment: Let your agent assign conversations to teams or admins, create new conversations, and close them when resolved, streamlining your support workflow.
  • Contact tagging and note creation: Effortlessly tag contacts with relevant labels or add detailed notes for context, making customer follow-ups more organized and actionable.
  • Automated company and contact updates: Enable your agent to attach contacts to companies, create or update company records, and keep your Intercom data clean and up to date.
  • Article and collection creation: Let your agent publish new articles or create help center collections to expand your self-serve support resources without manual effort.
  • Subscription and message preferences management: Allow your agent to add or manage subscriptions for contacts, helping you personalize communication and respect user preferences automatically.

Supported Tools & Triggers

Tools
Add subscription to a contactYou can add a specific subscription to a contact.
Add tag to a contactYou can tag a specific contact.
Assign conversationAssigns a conversation to a specific admin or team in intercom
Attach a contact to a companyYou can attach a company to a single contact.
Close conversationCloses a conversation in intercom, marking it as resolved
Create a collectionYou can create a new collection by making a post request to `https://api.
Create an articleYou can create a new article by making a post request to `https://api.
Create a noteYou can add a note to a single contact.
Create conversationCreates a new conversation in intercom
Create or update a companyYou can create or update a company.
Delete a collectionYou can delete a single collection by making a delete request to `https://api.
Delete a companyYou can delete a single company.
Delete a contactYou can delete a single contact.
Delete an articleYou can delete a single article by making a delete request to `https://api.
Detach a contact from a companyYou can detach a company from a single contact.
Get a contactYou can fetch the details of a single contact.
Get conversationRetrieves a specific conversation by id with all messages and details
Identify an adminYou can view the currently authorised admin along with the embedded app object (a "workspace" in legacy terminology).
List all activity logsYou can get a log of activities by all admins in an app.
List all adminsYou can fetch a list of admins for a given workspace.
List all articlesYou can fetch a list of all articles by making a get request to `https://api.
List all collectionsYou can fetch a list of all collections by making a get request to `https://api.
List all companiesYou can list companies.
List all help centersYou can list all help centers by making a get request to `https://api.
List all notesYou can fetch a list of notes that are associated to a contact.
List attached companies for contactYou can fetch a list of companies that are associated to a contact.
List attached contactsYou can fetch a list of all contacts that belong to a company.
List attached segments for companiesYou can fetch a list of all segments that belong to a company.
List attached segments for contactYou can fetch a list of segments that are associated to a contact.
List conversationsLists conversations from intercom with filtering and pagination support
List subscriptions for a contactYou can fetch a list of subscription types that are attached to a contact.
List tags attached to a contactYou can fetch a list of all tags that are attached to a specific contact.
Merge a lead and a userYou can merge a contact with a `role` of `lead` into a contact with a `role` of `user`.
Remove subscription from a contactYou can remove a specific subscription from a contact.
Remove tag from a contactYou can remove tag from a specific contact.
Reopen conversationReopens a closed conversation in intercom
Reply to conversationSends a reply to an existing conversation in intercom
Retrieve a collectionYou can fetch the details of a single collection by making a get request to `https://api.
Retrieve a company by idYou can fetch a single company.
Retrieve a help centerYou can fetch the details of a single help center by making a get request to `https://api.
Retrieve an adminYou can retrieve the details of a single admin.
Retrieve an articleYou can fetch the details of a single article by making a get request to `https://api.
Retrieve companiesYou can fetch a single company by passing in `company id` or `name`.
Scroll over all companiesThe `list all companies` functionality does not work well for huge datasets, and can result in errors and performance problems when paging deeply.
Search conversationsSearches for conversations using query string with support for filtering and sorting
Search for articlesYou can search for articles by making a get request to `https://api.
Set an admin to awayYou can set an admin as away for the inbox.
Update a collectionYou can update the details of a single collection by making a put request to `https://api.
Update a companyYou can update a single company using the intercom provisioned `id`.
Update a contactYou can update an existing contact (ie.
Update an articleYou can update the details of a single article by making a put request to `https://api.

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 Intercom 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 Intercom

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

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

Create the Mastra agent

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

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

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

FAQ

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

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

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

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

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Letta
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HubSpot
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Letta
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HubSpot
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Altera
DataStax
Entelligence
Rolai

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