How to integrate Typeform MCP with Mastra AI

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Introduction

This guide walks you through connecting Typeform to Mastra AI using the Composio tool router. By the end, you'll have a working Typeform agent that can list all recent responses for a form, create a new form for event signup, export submissions from my survey to csv through natural language commands.

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

The Typeform MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Typeform account. It provides structured and secure access so your agent can perform Typeform operations on your behalf.

Supported Tools & Triggers

Tools
Create Account WorkspaceTool to create a new workspace in a specific Typeform account.
Create FormTool to create a new Typeform form with customizable fields, logic, and settings.
Create ImageTool to upload a new image to your Typeform account via base64 encoding or URL.
Create or Update WebhookTool to create a new webhook or update an existing one for a specified Typeform.
Create ThemeTool to create a new custom theme in Typeform with colors, fonts, background, and layout settings.
Create WorkspaceTool to create a new workspace in Typeform.
Delete FormTool to permanently delete a Typeform and all of its responses.
Delete ImageTool to delete an image from your Typeform account.
Delete ResponsesTool to delete specific responses from a Typeform by response IDs.
Delete ThemeTool to delete a theme from your Typeform account.
Delete WebhookTool to delete a webhook configuration from a Typeform form.
Delete WorkspaceTool to delete a workspace from your Typeform account.
Get About MeGet information about the owner account in Typeform.
Get All Response FilesTool to retrieve a compressed archive containing all files that respondents uploaded for a specified form.
Get Background By SizeTool to retrieve a background image by size from Typeform.
Get Choice Image By SizeTool to retrieve a choice image by size from Typeform.
Get FormTool to retrieve a specific form's complete configuration including fields, logic, settings, and theme.
Get Form MessagesTool to retrieve custom messages for a Typeform including button labels, error messages, and UI text.
Get Form ResponsesTool to retrieve form responses from Typeform with filtering by date, pagination, search, and response type.
Get Image By SizeTool to retrieve an image in a specific size from Typeform.
Get ThemeTool to retrieve a specific theme's configuration including colors, fonts, and layout settings.
Get WebhookTool to retrieve a single webhook by specifying both the form ID and webhook tag.
Get WorkspaceTool to retrieve detailed information about a specific workspace including its name, forms, and team members.
List FormsTool to retrieve a list of all forms in your Typeform account with filtering, pagination, and sorting options.
List ImagesTool to retrieve all images in your Typeform account in reverse-chronological order.
List Typeform ThemesTool to retrieve a paginated list of themes in your Typeform account.
List Form WebhooksTool to retrieve all webhooks associated with a specified typeform.
List WorkspacesTool to retrieve all workspaces in a Typeform account with their IDs, names, form counts, and members.
Patch FormTool to partially update a Typeform using JSON Patch operations.
Update Theme (Partial)Tool to partially update a Typeform theme by ID.
Update FormTool to update an existing Typeform by completely replacing its configuration.
Update Form MessagesTool to update custom messages for form UI elements like buttons, errors, and placeholders in Typeform.
Update ThemeTool to update a theme's complete definition in Typeform.
Update WorkspaceTool to update a workspace's name or manage team member access (add/remove members) in Typeform.
Upload VideoInitiate a video upload to Typeform by obtaining a signed upload URL.

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 Typeform 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 Typeform

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

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

Create the Mastra agent

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

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

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

OpenAI Agents SDK

OpenAI Agents SDK

Use Typeform MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Typeform MCP with Claude Agent SDK

Google ADK

Google ADK

Use Typeform MCP with Google ADK

LangChain

LangChain

Use Typeform MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Typeform MCP with Vercel AI SDK

LlamaIndex

LlamaIndex

Use Typeform MCP with LlamaIndex

CrewAI

CrewAI

Use Typeform MCP with CrewAI

Claude Code

Claude Code

Use Typeform MCP with Claude Code

Codex

Codex

Use Typeform MCP with Codex

FAQ

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

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

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

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

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