# How to integrate Formcarry MCP with Autogen

```json
{
  "title": "How to integrate Formcarry MCP with Autogen",
  "toolkit": "Formcarry",
  "toolkit_slug": "formcarry",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/formcarry/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/formcarry/framework/autogen.md",
  "updated_at": "2026-05-12T10:12:08.631Z"
}
```

## Introduction

This guide walks you through connecting Formcarry to AutoGen 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 AutoGen 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

- [OpenAI Agents SDK](https://composio.dev/toolkits/formcarry/framework/open-ai-agents-sdk)
- [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 required dependencies for Autogen and Composio
- Initialize Composio and create a Tool Router session for Formcarry
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Formcarry tools
- Run a live chat loop where you ask the agent to perform Formcarry operations

## What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.
Key features include:
- Multi-Agent Systems: Build collaborative agent workflows
- MCP Workbench: Native support for Model Context Protocol tools
- Streaming HTTP: Connect to external services through streamable HTTP
- AssistantAgent: Pre-built agent class for tool-using assistants

## 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 agents and assistants directly to Formcarry. Instead of manually wiring Formcarry APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
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

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Formcarry account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 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).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

Install Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Formcarry via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

Create a .env file in your project folder.
What's happening:
- COMPOSIO_API_KEY is required to talk to Composio
- OPENAI_API_KEY is used by Autogen's OpenAI client
- USER_ID is how Composio identifies which user's Formcarry connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Formcarry tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Formcarry session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["formcarry"]
    )
    url = session.mcp.url
```

### 5. Configure MCP parameters for Autogen

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.
What's happening:
- url points to the Tool Router MCP endpoint from Composio
- timeout is the HTTP timeout for requests
- sse_read_timeout controls how long to wait when streaming responses
- terminate_on_close=True cleans up the MCP server process when the workbench is closed
```python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Formcarry tools from the workbench
```python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Formcarry assistant agent with MCP tools
    agent = AssistantAgent(
        name="formcarry_assistant",
        description="An AI assistant that helps with Formcarry operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Formcarry tools to call via MCP
- agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
- Typing exit, quit, or bye ends the loop
```python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Formcarry related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
```

## Complete Code

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

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Formcarry session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["formcarry"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Formcarry assistant agent with MCP tools
        agent = AssistantAgent(
            name="formcarry_assistant",
            description="An AI assistant that helps with Formcarry operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Formcarry related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

## Conclusion

You now have an Autogen assistant wired into Formcarry through Composio's Tool Router and MCP. From here you can:
- Add more toolkits to the toolkits list, for example notion or hubspot
- Refine the agent description to point it at specific workflows
- Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Formcarry, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Formcarry MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/formcarry/framework/open-ai-agents-sdk)
- [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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## 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 Autogen?

Yes, you can. Autogen 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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