# How to integrate Tally MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Tally MCP with OpenAI Agents SDK",
  "toolkit": "Tally",
  "toolkit_slug": "tally",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/tally/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/tally/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:27:52.163Z"
}
```

## Introduction

This guide walks you through connecting Tally to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Tally agent that can list all forms i created this month, download latest responses from your survey form, add a webhook to notify on new submission through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK 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 Agent SDK](https://composio.dev/toolkits/tally/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/tally/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/tally/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/tally/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/tally/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/tally/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/tally/framework/cli)
- [Google ADK](https://composio.dev/toolkits/tally/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/tally/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/tally/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/tally/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/tally/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/tally/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the necessary dependencies
- Initialize Composio and create a Tool Router session for Tally
- Configure an AI agent that can use Tally as a tool
- Run a live chat session where you can ask the agent to perform Tally operations

## What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.
Key features include:
- Hosted MCP Tools: Connect to external services through hosted MCP endpoints
- SQLite Sessions: Persist conversation history across interactions
- Simple API: Clean interface with Agent, Runner, and tool configuration
- Streaming Support: Real-time response streaming for interactive applications

## 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.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `TALLY_CREATE_FORM` | Create Form | Tool to create a new form. Use after preparing block definitions and optional settings. |
| `TALLY_CREATE_WEBHOOK` | Create Webhook | Tool to create a new webhook for a form. Use after confirming you have the form ID and the callback URL. |
| `TALLY_DELETE_FORM` | Delete Form | Tool to delete a specific form identified by its ID. Use after confirming the form should be permanently removed. |
| `TALLY_DELETE_WEBHOOK` | Delete Webhook | Tool to delete a specific webhook. Use after confirming the webhook ID. |
| `TALLY_GET_FORM_DETAILS` | Get Form Details | Tool to retrieve details of a specific form. Use when you need comprehensive form metadata by ID. Use after confirming the form ID to fetch its full configuration, blocks, and stats. |
| `TALLY_GET_FORM_RESPONSES` | Get Form Responses | Tool to retrieve the responses of a specific form. Use after confirming the form ID and when paginated data is needed. |
| `TALLY_GET_USER_INFO` | Get User Info | Tool to retrieve information about the authenticated user. Use when you need to confirm account-level details before proceeding. Returns account/workspace context only — not form-level access; follow up with TALLY_LIST_FORMS to verify form access. Confirm the returned workspace and user context match the intended account before creating or modifying resources, as acting on the wrong context places resources in an unintended account. Do not expose sensitive response fields (e.g., tokens) in user-visible output. |
| `TALLY_GET_WEBHOOK_EVENTS` | Get Webhook Events | Tool to list events associated with a specific webhook. Use when you need to inspect delivery history after creating or listing a webhook. |
| `TALLY_GET_WORKSPACE` | Get Workspace | Tool to retrieve a single workspace by its ID with associated members. Use when you need to get detailed information about a specific workspace. |
| `TALLY_LIST_FORM_QUESTIONS` | List Form Questions | Tool to retrieve all questions from a specific form. Use when you need to list all questions and their structure after obtaining the form ID. |
| `TALLY_LIST_FORMS` | List Forms | Tool to retrieve a paginated list of forms. Use when you need to list all forms accessible to the authenticated user. |
| `TALLY_LIST_ORGANIZATION_INVITES` | List Organization Invites | Tool to retrieve all pending invites in your organization. Use when you need to view or manage organization invitation status. |
| `TALLY_LIST_ORGANIZATION_USERS` | List Organization Users | Tool to retrieve all users in an organization. Use when you need to list organization members or check user permissions. |
| `TALLY_LIST_WEBHOOKS` | List Webhooks | Tool to retrieve a paginated list of configured webhooks. Use when you need a full listing of webhooks across your accessible forms and workspaces. |
| `TALLY_LIST_WORKSPACES` | List Workspaces | Tool to retrieve a paginated list of workspaces. Use when you need to browse workspaces accessible to the authenticated user. |
| `TALLY_UPDATE_FORM` | Update Form | Tool to update form details. Use after confirming the form exists and obtaining its ID. |
| `TALLY_UPDATE_WEBHOOK` | Update Webhook | Tool to update an existing webhook configuration. Use when you need to modify webhook settings such as URL, event types, or enable/disable status. |
| `TALLY_UPDATE_WORKSPACE` | Update Workspace | Tool to update the details of a specific workspace identified by its ID. Use when you need to rename a workspace after confirming the workspace ID. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Tally MCP server is an implementation of the Model Context Protocol that connects your AI agent to Tally. It provides structured and secure access so your agent can perform Tally operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live Tally project
- Some knowledge of Python or Typescript

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider.
- Keep the API key safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

What's happening:
- You're importing all necessary libraries.
- The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Tally.
```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only tally.
- The router checks the user's Tally connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Tally.
- This approach keeps things lightweight and lets the agent request Tally tools only when needed during the conversation.
```python
# Create a Tally Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["tally"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Tally
const session = await composio.create(userId as string, {
  toolkits: ['tally'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Tally. "
        "Help users perform Tally operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Tally. Help users perform Tally operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["tally"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Tally. "
        "Help users perform Tally operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['tally'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Tally. Help users perform Tally operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});
```

## Conclusion

This was a starter code for integrating Tally MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Tally.
Key features:
- Hosted MCP tool integration through Composio's Tool Router
- SQLite session persistence for conversation history
- Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

## How to build Tally MCP Agent with another framework

- [Claude Agent SDK](https://composio.dev/toolkits/tally/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/tally/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/tally/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/tally/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/tally/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/tally/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/tally/framework/cli)
- [Google ADK](https://composio.dev/toolkits/tally/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/tally/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/tally/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/tally/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/tally/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/tally/framework/crew-ai)

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- [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots.
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- [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows.
- [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses.
- [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research.
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- [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation.
- [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Tally MCP?

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.

### Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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.

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

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.

### 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 Tally data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)