How to integrate Formbricks MCP with LangChain

This guide walks you through connecting Formbricks to LangChain using the Composio tool router. By the end, you'll have a working Formbricks agent that can create a new customer feedback survey, add a contact to our user list, record survey responses from yesterday's event through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Formbricks account through Composio's Formbricks MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Formbricks logoFormbricks
Api Key

Formbricks is an open-source platform for building and managing surveys. It helps organizations collect and analyze user feedback efficiently.

45 Tools

Introduction

This guide walks you through connecting Formbricks to LangChain using the Composio tool router. By the end, you'll have a working Formbricks agent that can create a new customer feedback survey, add a contact to our user list, record survey responses from yesterday's event through natural language commands.

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

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

Also integrate Formbricks with

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Formbricks project to Composio
  • Create a Tool Router MCP session for Formbricks
  • Initialize an MCP client and retrieve Formbricks tools
  • Build a LangChain agent that can interact with Formbricks
  • 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 Formbricks MCP server, and what's possible with it?

The Formbricks MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Formbricks account. It provides structured and secure access to your survey management tools, so your agent can perform actions like creating surveys, collecting responses, managing contacts, and handling webhooks automatically on your behalf.

  • Survey creation and management: Easily instruct your agent to create new surveys, define questions, and set up feedback forms tailored to your needs.
  • Automated response collection: Have your agent log responses to surveys, link displays to responses, and streamline data gathering effortlessly.
  • Contact and attribute management: Direct your agent to add or remove contacts, create or delete attribute classes, and segment audiences for more targeted feedback analysis.
  • Webhook configuration for real-time events: Let your agent register new webhooks to automatically send survey response data to external systems or endpoints.
  • Cleanup and maintenance tools: Authorize your agent to delete surveys, survey responses, persons, or unused attributes, keeping your Formbricks workspace organized and 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 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 Formbricks 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 Formbricks 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: ['formbricks']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Formbricks 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 Formbricks tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "formbricks-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 Formbricks MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Formbricks 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 Formbricks 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 Formbricks 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: ['formbricks']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "formbricks-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 Formbricks 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 Formbricks 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 Formbricks action and event your agent gets out of the box.

Check Health

Tool to check the health status of the Formbricks API.

Create Action Class

Tool to create a new action class.

Create Attribute Class

Creates a new attribute class (custom contact attribute) in Formbricks.

Create Client User

Tool to create or identify a user within a specified environment.

Create Contact

Creates a new contact in a Formbricks environment.

Create Display

Create a display record to track when a survey is shown to users.

Create Survey Response

Tool to create a response for a survey.

Create Survey

Tool to create a new survey.

Create Webhook

Tool to create a new webhook.

Delete Attribute Class

Tool to delete an attribute class.

Delete Person

Tool to delete a person.

Delete Survey Response

Tool to delete a survey response by its ID.

Delete Survey

Deletes a survey from Formbricks by its unique identifier.

Delete Team

Tool to delete an organization team by its ID.

Delete Webhook

Tool to delete a webhook by ID.

Get Account Info

Retrieves environment information for the authenticated API key.

Get All Contacts

Tool to retrieve all contacts within the organization.

Get Attribute Class

Tool to get a specific attribute class by ID.

Get Client Contacts State

Tool to get the current state of a contact including surveys and segment information.

Get Contact Attribute Key

Tool to retrieve detailed information about a specific contact attribute key by ID (v2 API).

Get Contact by ID

Tool to retrieve a specific contact by its ID.

Get Me

Tool to retrieve current authenticated organization's and environment details.

Get Person by ID

Tool to retrieve a person by their internal ID in Formbricks.

Get Responses

Retrieve survey responses with flexible filtering, sorting, and pagination.

Get Roles

Tool to retrieve all available roles in the system.

Get Webhook

Tool to retrieve details of a specific webhook.

List Action Classes

List all action classes in your Formbricks environment.

List Attribute Classes

Tool to list all attribute classes.

List Client Environment

Tool to retrieve environment state for Formbricks SDKs.

List Contact Attribute Keys

Tool to retrieve contact attribute keys from Formbricks.

List Health

Tool to check the health status of critical application dependencies including database and cache.

List Management Contact Attributes

Tool to retrieve all contact attributes in the environment.

List Management Me

Tool to retrieve authenticated user's environment and project information.

List Management People

Tool to retrieve all people (legacy term for contacts) in the environment.

List Organizations Project Teams

Tool to list all project-team assignments for an organization (v2 API only).

List Organization Teams

Tool to retrieve all teams in an organization (v2 API).

List Surveys

List all surveys in the environment.

List Webhooks

List all webhooks configured for the current environment.

Update Contact Attributes

Tool to update a contact's attributes in Formbricks.

Update Survey Response

Tool to update an existing survey response.

Update Survey

Updates an existing Formbricks survey with new properties.

Update Webhook

Tool to update an existing webhook.

Upload Bulk Contacts

Upload multiple contacts to a Formbricks environment in bulk (up to 250 per request).

Upload Private File

Tool to obtain S3 presigned upload data for a private survey file.

Upload Public File

Retrieves S3 presigned upload URLs and form fields for uploading a public file to Formbricks storage.

FAQ

Frequently asked questions

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

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

Start with Formbricks.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Formbricks tool your agent needs.Free to start.

Start building