How to integrate Iterate MCP with LangChain

This guide walks you through connecting Iterate to LangChain 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 LangChain 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 LangChain 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 LangChain 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 ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Iterate project to Composio
  • Create a Tool Router MCP session for Iterate
  • Initialize an MCP client and retrieve Iterate tools
  • Build a LangChain agent that can interact with Iterate
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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 step10 STEPS
1

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI 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

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • @composio/langchain provides Composio integration for LangChain
  • @langchain/mcp-adapters enables MCP client connections
  • @langchain/core is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_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 your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Iterate functionality through MCP
6

Initialize Composio client

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

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Iterate tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['iterate']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Iterate 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
  • This approach allows the agent to dynamically load and use Iterate tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "iterate-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Iterate MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Iterate tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

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

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

rl.prompt();

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

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

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

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

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

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

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

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['iterate']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "iterate-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Iterate related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\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

You've successfully built a LangChain agent that can interact with Iterate through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.
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

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

CrewAI logo

CrewAI

Use Iterate MCP with CrewAI

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. LangChain 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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