How to integrate Survey monkey MCP with Pydantic AI

This guide walks you through connecting Survey monkey to Pydantic AI using the Composio tool router. By the end, you'll have a working Survey monkey agent that can create a survey titled 'employee feedback', list all surveys from last month, get responses for the 'customer satisfaction' survey through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Survey monkey account through Composio's Survey monkey MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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SurveyMonkey is an online survey platform for building, distributing, and analyzing surveys. It helps organizations collect feedback and gain actionable insights fast.

22 Tools

Introduction

This guide walks you through connecting Survey monkey to Pydantic AI using the Composio tool router. By the end, you'll have a working Survey monkey agent that can create a survey titled 'employee feedback', list all surveys from last month, get responses for the 'customer satisfaction' survey through natural language commands.

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

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

Also integrate Survey monkey with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Survey monkey
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Survey monkey workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

What is the Survey monkey MCP server, and what's possible with it?

The Survey monkey MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your SurveyMonkey account. It provides structured and secure access to your surveys and data, so your agent can create surveys, distribute them, analyze responses, and manage contacts on your behalf.

  • Survey creation and management: Quickly instruct your agent to create new surveys for any purpose or delete surveys you no longer need.
  • Survey distribution control: Retrieve and manage collector links and distribution channels so your agent can help you share surveys with the right people.
  • Real-time response analysis: Fetch detailed survey responses and metadata, enabling your agent to analyze feedback and generate insights instantly.
  • Contact and group coordination: Access and manage your SurveyMonkey contacts and groups, letting your agent organize recipients and streamline survey delivery.
  • Survey inventory and details lookup: List all your surveys or fetch specific details and counts for any survey, making it easy for your agent to keep you up-to-date.

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:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Survey monkey
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Survey monkey
  • MCPServerStreamableHTTP connects to the Survey monkey MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Survey monkey
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["survey_monkey"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Survey monkey tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
survey_monkey_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[survey_monkey_mcp],
    instructions=(
        "You are a Survey monkey assistant. Use Survey monkey tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Survey monkey endpoint
  • The agent uses GPT-5 to interpret user commands and perform Survey monkey operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Survey monkey.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Survey monkey API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Survey monkey and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Survey monkey
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["survey_monkey"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    survey_monkey_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[survey_monkey_mcp],
        instructions=(
            "You are a Survey monkey assistant. Use Survey monkey tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Survey monkey.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

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

Conclusion

You've built a Pydantic AI agent that can interact with Survey monkey through Composio's Tool Router. With this setup, your agent can perform real Survey monkey actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Survey monkey for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

Every Survey monkey action and event your agent gets out of the box.

Create Bulk Contacts

Creates multiple contacts in SurveyMonkey in a single API call.

Create Contact

Creates a new contact in SurveyMonkey.

Create Contact List

Creates a new contact list in SurveyMonkey.

Create Survey

Creates a new empty survey in SurveyMonkey with one empty page and no questions.

Create Survey Folder

Creates a new survey folder in SurveyMonkey to organize surveys.

Delete Survey

Tool to delete a specific survey.

Bulk Get Contacts

Tool to retrieve contacts in bulk from SurveyMonkey.

Get Survey Collectors

Tool to retrieve a list of collectors for a specific survey.

Get Contacts

Retrieves a list of contacts from SurveyMonkey.

Get Current User

Tool to retrieve the current authenticated user's account details including plan information.

Get Groups

Tool to retrieve a list of groups.

Get Survey Responses

Tool to retrieve a paginated list of responses for a specific survey.

Get Survey Details

Retrieves comprehensive details and metadata for a specific survey by its ID.

Get Survey Details (Expanded)

Retrieves expanded survey details including all pages, questions, and answer options.

Get Survey Responses (Bulk)

Tool to retrieve bulk survey responses with full question answers and response data.

Get Surveys

Tool to retrieve a paginated list of surveys.

Get Survey Trends

Tool to retrieve trend data for a survey showing answer counts for particular time periods.

List Available Languages

Tool to retrieve all available languages for creating multilingual surveys.

List Benchmark Bundles

Tool to retrieve a list of benchmark bundles.

List Contact Fields

Tool to retrieve a list of contact fields from SurveyMonkey.

List Contact Lists

Tool to retrieve a list of contact lists from SurveyMonkey.

List Webhooks

Tool to retrieve a list of webhooks from SurveyMonkey.

FRAMEWORKS

How to build Survey monkey MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Survey monkey MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Survey monkey MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Survey monkey MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Survey monkey MCP with Claude Cowork

Codex logo

Codex

Use Survey monkey MCP with Codex

OpenClaw logo

OpenClaw

Use Survey monkey MCP with OpenClaw

Hermes logo

Hermes

Use Survey monkey MCP with Hermes

CLI logo

CLI

Use Survey monkey MCP with CLI

Google ADK logo

Google ADK

Use Survey monkey MCP with Google ADK

LangChain logo

LangChain

Use Survey monkey MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Survey monkey MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Survey monkey MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Survey monkey MCP with LlamaIndex

CrewAI logo

CrewAI

Use Survey monkey MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Survey monkey MCP server, the agents and LLMs can only access a fixed set of Survey monkey tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Survey monkey and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Pydantic 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 Survey monkey tools.

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

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