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How to integrate Tally MCP with Mastra AI

Connect Mastra AI to Tally MCP. List all forms i created this month, download latest responses from your survey form, and more using natural language, with authentication handled for you.

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Tally is a flexible online form builder for creating surveys, quizzes, and data collection tools. Its intuitive interface makes it easy to gather and manage responses without coding.

18 Tools

Introduction

This guide walks you through connecting Tally to Mastra AI using the Composio tool router. By the end, you'll have a working Tally agent that can create and update forms, fetch form responses, list questions, manage workspaces, and set up webhooks through natural language commands.

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

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

Also integrate Tally with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKLlamaIndexCrewAIPydantic AIAutoGen

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

The Tally MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Tally account. It provides structured and secure access to your forms and response data, so your agent can perform actions like creating forms, retrieving responses, managing webhooks, and automating data collection workflows on your behalf.

  • Automated form creation and management: Have your agent create new forms, update existing ones, or delete forms as needed—no manual setup required.
  • Seamless response collection and analysis: Instantly fetch all responses to any form, enabling real-time data analysis, exports, or notifications.
  • Detailed form insights and field discovery: Retrieve comprehensive details about a form’s configuration, fields, and settings to power dynamic workflows or audits.
  • Webhook automation and event monitoring: Set up and manage webhooks to trigger custom actions when new responses come in, and review delivery history for full visibility.
  • User account and access checks: Let your agent fetch authenticated user info to confirm account status or permissions before performing sensitive operations.

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 Tally 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 Tally

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

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

Create the Mastra agent

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

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

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

Create Form

Tool to create a new form.

Create Webhook

Tool to create a new webhook for a form.

Delete Form

Delete a specific form by ID, moving it to the trash.

Delete Webhook

Delete a specific webhook by ID.

Get Form Details

Retrieve a form by ID, including its blocks, submission count, metadata, and supported settings.

Get Form Responses

Retrieve a page of submissions and responses for a specific form.

Get User Info

Retrieve account information for the authenticated user, including their organization ID.

Get Webhook Events

Tool to list events associated with a specific webhook.

Get Workspace

Tool to retrieve a single workspace by its ID with associated members.

List Form Questions

Tool to retrieve all questions from a specific form.

List Forms

Tool to retrieve a paginated list of forms.

List Organization Invites

Tool to retrieve all pending invites in your organization.

List Organization Users

Retrieve users in an organization by organization ID.

List Webhooks

Tool to retrieve a paginated list of configured webhooks.

List Workspaces

Tool to retrieve a paginated list of workspaces.

Update Form

Tool to update form details.

Update Webhook

Update an existing webhook configuration, including its URL, event types and enabled status.

Update Workspace

Tool to update the details of a specific workspace identified by its ID.

FRAMEWORKS

How to build Tally MCP Agent with another framework

Claude Code logo

Claude Code

Use Tally MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Tally MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Tally MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Tally MCP with Claude Agent SDK

Codex logo

Codex

Use Tally MCP with Codex

OpenClaw logo

OpenClaw

Use Tally MCP with OpenClaw

Hermes logo

Hermes

Use Tally MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Tally MCP with Atomic Agent

Google ADK logo

Google ADK

Use Tally MCP with Google ADK

LangChain logo

LangChain

Use Tally MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Tally MCP with Vercel AI SDK

LlamaIndex logo

LlamaIndex

Use Tally MCP with LlamaIndex

CrewAI logo

CrewAI

Use Tally MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Tally MCP with Pydantic AI

AutoGen logo

AutoGen

Use Tally MCP with AutoGen

FAQ

Frequently asked questions

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

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

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