# How to integrate Formcarry MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Formcarry MCP with OpenAI Agents SDK",
  "toolkit": "Formcarry",
  "toolkit_slug": "formcarry",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/formcarry/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/formcarry/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:12:08.631Z"
}
```

## Introduction

This guide walks you through connecting Formcarry to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Formcarry agent that can show all submissions from contact form, list feedback form responses from last week, retrieve job application submissions with resumes through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Formcarry account through Composio's Formcarry MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Formcarry with

- [Claude Agent SDK](https://composio.dev/toolkits/formcarry/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/formcarry/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/formcarry/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/formcarry/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/formcarry/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/formcarry/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/formcarry/framework/cli)
- [Google ADK](https://composio.dev/toolkits/formcarry/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/formcarry/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/formcarry/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/formcarry/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/formcarry/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/formcarry/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 Formcarry
- Configure an AI agent that can use Formcarry as a tool
- Run a live chat session where you can ask the agent to perform Formcarry 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 Formcarry MCP server, and what's possible with it?

The Formcarry MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Formcarry account. It provides structured and secure access to your form submissions, so your agent can perform actions like retrieving submissions, filtering response data, and automating workflows based on incoming form entries on your behalf.
- Retrieve recent form submissions: Instantly pull the latest entries from any of your Formcarry forms, complete with all submitted data.
- Filter submissions by form ID: Ask your agent to search and fetch submissions for a specific form, making it easy to review targeted data.
- Paginate through large datasets: Effortlessly process high volumes of submissions by navigating through paginated form responses.
- Automate form response processing: Use your agent to analyze new submissions and trigger follow-up actions or integrations without manual effort.
- Monitor submission trends over time: Let your agent help you track, summarize, and act on patterns in incoming form data.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `FORMCARRY_CREATE_FORM` | Create Form | Create a new form with customizable settings including email notifications, webhooks, and thank you pages. This action creates a Formcarry form with extensive configuration options for email notifications (both to form owners and respondents), webhook integrations, Google Recaptcha spam protection, and customizable thank you pages. Use when you need to programmatically set up a new form with specific notification rules or integrations. |
| `FORMCARRY_DELETE_FORM` | Delete Form | Delete an existing form by its Form ID. Use when you need to permanently remove a form from your Formcarry account. |
| `FORMCARRY_RETRIEVE_SUBMISSIONS` | Retrieve Form Submissions | Retrieves all submissions for a specific Formcarry form. Returns a paginated list of form submissions with their field data, timestamps, and submission IDs. Use pagination parameters to navigate through large submission sets. Default page size is 25, maximum is 50 submissions per page. Useful for: collecting form responses, exporting submission data, integrating form data into other systems, or building custom analytics dashboards. |
| `FORMCARRY_VERIFY_AUTH` | Verify API Key Authentication | Tool to verify API key authentication with Formcarry. Use this endpoint to check if your API key is valid before making other API requests. Returns success status and a confirmation message if the API key is valid. |

## Supported Triggers

None listed.

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

The Formcarry MCP server is an implementation of the Model Context Protocol that connects your AI agent to Formcarry. It provides structured and secure access so your agent can perform Formcarry 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 Formcarry 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 Formcarry.
```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 formcarry.
- The router checks the user's Formcarry connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Formcarry.
- This approach keeps things lightweight and lets the agent request Formcarry tools only when needed during the conversation.
```python
# Create a Formcarry Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["formcarry"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Formcarry
const session = await composio.create(userId as string, {
  toolkits: ['formcarry'],
});
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 Formcarry. "
        "Help users perform Formcarry 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 Formcarry. Help users perform Formcarry 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=["formcarry"]
)
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 Formcarry. "
        "Help users perform Formcarry 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: ['formcarry'],
  });
  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 Formcarry. Help users perform Formcarry 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 Formcarry MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Formcarry.
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 Formcarry MCP Agent with another framework

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

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- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
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- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
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## Frequently Asked Questions

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

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

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

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

---
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