# How to integrate Fillout forms MCP with LangChain

```json
{
  "title": "How to integrate Fillout forms MCP with LangChain",
  "toolkit": "Fillout forms",
  "toolkit_slug": "fillout_forms",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/fillout_forms/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/fillout_forms/framework/langchain.md",
  "updated_at": "2026-05-06T08:11:33.153Z"
}
```

## Introduction

This guide walks you through connecting Fillout forms to LangChain using the Composio tool router. By the end, you'll have a working Fillout forms agent that can list all your active fillout forms, show details for your latest created form, invalidate api token for fillout account through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Fillout forms account through Composio's Fillout forms MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Fillout forms with

- [OpenAI Agents SDK](https://composio.dev/toolkits/fillout_forms/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/fillout_forms/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/fillout_forms/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/fillout_forms/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/fillout_forms/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/fillout_forms/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/fillout_forms/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/fillout_forms/framework/cli)
- [Google ADK](https://composio.dev/toolkits/fillout_forms/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/fillout_forms/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/fillout_forms/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/fillout_forms/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/fillout_forms/framework/crew-ai)

## TL;DR

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

The Fillout forms MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Fillout account. It provides structured and secure access to your forms and form management tools, so your agent can fetch form data, list all your forms, manage authorization, and help automate form workflows on your behalf.
- Comprehensive form listing: Instantly retrieve and display a list of all forms in your Fillout account, making it easy to review and manage your surveys and data collection tools.
- Seamless authorization management: Let your agent handle the OAuth authorization flow for securely connecting third-party applications to your Fillout account—no manual steps required.
- Token revocation and security: Instruct your agent to programmatically invalidate or revoke access tokens, ensuring that only trusted applications and users have access to your Fillout data.
- Automated workflow integration: Use your agent to connect Fillout forms with other apps or workflows, streamlining data collection and processing without manual intervention.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `FILLOUT_FORMS_AUTHORIZE_O_AUTH` | Authorize OAuth | Tool to initiate the oauth authorization process for third-party applications. use when you need to generate the url to redirect your users to the fillout consent page. |
| `FILLOUT_FORMS_GET_FORMS` | Get forms | Tool to retrieve a list of all forms in your account. use when you need to list your forms after authenticating with fillout. |
| `FILLOUT_FORMS_INVALIDATE_ACCESS_TOKEN` | Invalidate Access Token | Tool to revoke an existing oauth access token. use when the user logs out or you need to programmatically invalidate a token after deauthorization. example: "invalidate token abcdefg123456". this endpoint does not return a json body. successful calls return http 200 or 204. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Fillout forms MCP server is an implementation of the Model Context Protocol that connects your AI agent to Fillout forms. It provides structured and secure access so your agent can perform Fillout forms operations on your behalf through a secure, permission-based interface.
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

No description provided.

### 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

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

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

### 3. Set up environment variables

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
```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
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
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();
```

### 5. Initialize Composio client

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 Fillout forms tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
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()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Fillout forms 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 Fillout forms tools as needed
```python
# Create Tool Router session for Fillout forms
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['fillout_forms']
)

url = session.mcp.url
```

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

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "fillout_forms-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "fillout_forms-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 });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

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

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

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

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Fillout forms 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);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['fillout_forms']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "fillout_forms-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Fillout forms related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

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

```typescript
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: ['fillout_forms']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "fillout_forms-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 Fillout forms 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 Fillout forms 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.

## How to build Fillout forms MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/fillout_forms/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/fillout_forms/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/fillout_forms/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/fillout_forms/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/fillout_forms/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/fillout_forms/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/fillout_forms/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/fillout_forms/framework/cli)
- [Google ADK](https://composio.dev/toolkits/fillout_forms/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/fillout_forms/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/fillout_forms/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/fillout_forms/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/fillout_forms/framework/crew-ai)

## Related Toolkits

- [Apilio](https://composio.dev/toolkits/apilio) - Apilio is a home automation platform that lets you connect and control smart devices from different brands. It helps you build flexible automations with complex conditions, schedules, and integrations.
- [Basin](https://composio.dev/toolkits/basin) - Basin is a no-code form backend for quickly setting up reliable contact forms. It lets you collect and manage form submissions without writing any server-side code.
- [Bouncer](https://composio.dev/toolkits/bouncer) - Bouncer is an email validation platform that verifies the authenticity of email addresses in real-time and batch. It helps boost deliverability and reduce bounce rates for your communications.
- [Conveyor](https://composio.dev/toolkits/conveyor) - Conveyor is a platform that automates security reviews with a Trust Center and AI-driven questionnaire automation. It streamlines compliance and vendor security processes for faster, hassle-free reviews.
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- [Faraday](https://composio.dev/toolkits/faraday) - Faraday lets you embed AI in workflows across your stack for smarter automation. It boosts your favorite tools with actionable intelligence and seamless integration.
- [Feathery](https://composio.dev/toolkits/feathery) - Feathery is an AI-powered platform for building dynamic data intake forms with advanced logic. It helps teams automate complex workflows and collect structured data with ease.
- [Formdesk](https://composio.dev/toolkits/formdesk) - Formdesk is an online form builder for creating and managing professional forms. It's perfect for collecting data, automating workflows, and integrating form submissions with your favorite services.
- [Formsite](https://composio.dev/toolkits/formsite) - Formsite lets you build online forms and surveys with drag-and-drop simplicity. Capture, manage, and integrate form responses securely for streamlined workflows.
- [Graphhopper](https://composio.dev/toolkits/graphhopper) - GraphHopper is an enterprise-grade Directions API for routing, optimization, and geocoding across multiple vehicle types. It enables fast, reliable route planning and logistics automation for businesses.
- [Hyperbrowser](https://composio.dev/toolkits/hyperbrowser) - Hyperbrowser is a next-generation platform for scalable browser automation. It empowers AI agents to interact with web apps, automate workflows, and handle browser sessions at scale.
- [La Growth Machine](https://composio.dev/toolkits/lagrowthmachine) - La Growth Machine automates multi-channel sales outreach and routine tasks for sales teams. Streamline your workflow and focus on closing more deals.
- [Leverly](https://composio.dev/toolkits/leverly) - Leverly is a workflow automation platform that connects and coordinates actions across your apps. It streamlines repetitive processes so your business runs smoother, faster, and with fewer manual steps.
- [Maintainx](https://composio.dev/toolkits/maintainx) - Maintainx is a cloud-based CMMS for centralizing maintenance data, communication, and workflows. It helps organizations streamline maintenance operations and improve team coordination.
- [Make](https://composio.dev/toolkits/make) - Make is an automation platform that connects your favorite apps and services. Build powerful, custom workflows without writing code.
- [Ntfy](https://composio.dev/toolkits/ntfy) - Ntfy is a notification service to send push messages to phones or desktops. Instantly deliver alerts and updates to users, devices, or teams.
- [Persona](https://composio.dev/toolkits/persona) - Persona offers identity infrastructure to automate user verification and compliance. It helps organizations securely verify users and reduce fraud risk.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Fillout forms MCP?

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

### Can I use Tool Router MCP with LangChain?

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 Fillout forms tools.

### Can I manage the permissions and scopes for Fillout forms while using Tool Router?

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

---
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