How to integrate Iterate MCP with CrewAI

This guide walks you through connecting Iterate to CrewAI using the Composio tool router. By the end, you'll have a working Iterate agent that can list your surveys, add survey recipients, review responses, search company users, and delete user data through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Iterate account through Composio's Iterate MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Iterate is a customer feedback platform for distributing surveys, analyzing responses, and managing user privacy data. It helps teams collect customer feedback, spot trends, and keep privacy workflows organized.

13 Tools

Introduction

This guide walks you through connecting Iterate to CrewAI using the Composio tool router. By the end, you'll have a working Iterate agent that can list your surveys, add survey recipients, review responses, search company users, and delete user data through natural language commands.

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

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

Also integrate Iterate with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Iterate connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Iterate
  • Build a conversational loop where your agent can execute Iterate operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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

The Iterate MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Iterate account. It provides structured and secure access to your surveys, recipients, responses, statistics, and company user data, so your agent can distribute surveys, review feedback, analyze performance, find users, and manage privacy requests on your behalf.

  • Survey distribution: Have your agent add one recipient or import a batch, then send the survey now or schedule it for later.
  • Survey review: Let the agent list your surveys and retrieve a survey's configuration and questions.
  • Feedback analysis: Instruct your agent to review completed submissions, inspect individual answers within a date range, and check delivery, response count, and response rate statistics.
  • Company user search: Direct your agent to find a company user by email, external reference, or profile property and review their survey participation totals.
  • Privacy data management: Have your agent anonymize identifying details while retaining responses, or permanently delete selected users and their survey responses.

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 step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Iterate connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
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 crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Iterate via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
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_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
5

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Iterate MCP URL
6

Create a Composio Tool Router session for Iterate

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["iterate"])

url = session.mcp.url
What's happening:
  • You create a Iterate only session through Composio
  • Composio returns an MCP HTTP URL that exposes Iterate tools
7

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
8

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Iterate and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["iterate"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Iterate through Composio's Tool Router. The agent can perform Iterate operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations
TOOLS

Supported Tools

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

Add Survey Recipient

Add one email recipient to a survey for a later send without sending the survey now.

Anonymize Company User

Irreversibly remove one Iterate user's email and attributes while retaining survey responses.

Bulk Anonymize Company Users

Irreversibly remove identifying data from every Iterate company user matching at least one explicit email, external-ID, or typed user-property selector while retaining survey responses.

Bulk Delete Company User Data

Permanently delete every matching Iterate company user and all matching users' survey responses using explicit non-empty selectors.

Delete Company User Data

Permanently delete one Iterate user object and all of that user's survey responses.

Get Survey

Return one survey's configuration and questions by survey ID.

Get Survey Stats

Return delivery, display, response-count, and response-rate statistics for one survey.

Import Survey Recipients

Add a non-empty batch of email recipients to a survey without sending it, and return duplicate, failure, and success counts.

List Survey Response Groups

Return one reverse-chronological page of completed survey submissions grouped by user, plus a continuation cursor.

List Survey Responses

Return one reverse-chronological page of individual answers for a survey, with an optional date range and continuation cursor.

List Surveys

Return all surveys available to the connected Iterate API key, including the survey and company IDs needed by other tools.

Search Company Users

Find one user in the connected Iterate company by email, external ID, or one typed user property and return survey participation totals.

Send Survey

Irreversibly send or schedule an email survey to one specified recipient or every previously added recipient.

FRAMEWORKS

How to build Iterate MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Iterate MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Iterate MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Iterate MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Iterate MCP with Claude Cowork

Codex logo

Codex

Use Iterate MCP with Codex

OpenClaw logo

OpenClaw

Use Iterate MCP with OpenClaw

Hermes logo

Hermes

Use Iterate MCP with Hermes

CLI logo

CLI

Use Iterate MCP with CLI

Google ADK logo

Google ADK

Use Iterate MCP with Google ADK

LangChain logo

LangChain

Use Iterate MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Iterate MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Iterate MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Iterate MCP with LlamaIndex

FAQ

Frequently asked questions

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

Yes, you can. CrewAI 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 Iterate tools.

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

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