How to integrate Bubble MCP with LangChain

This guide walks you through connecting Bubble to LangChain using the Composio tool router. By the end, you'll have a working Bubble agent that can create a new user in your bubble app, update a record in the bubble database, fetch all orders from your bubble store through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Bubble account through Composio's Bubble MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Bubble is a visual programming platform for building web apps without code. It empowers anyone to create, launch, and scale interactive applications quickly.

15 Tools

Introduction

This guide walks you through connecting Bubble to LangChain using the Composio tool router. By the end, you'll have a working Bubble agent that can create a new user in your bubble app, update a record in the bubble database, fetch all orders from your bubble store through natural language commands.

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

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

Also integrate Bubble 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 Bubble project to Composio
  • Create a Tool Router MCP session for Bubble
  • Initialize an MCP client and retrieve Bubble tools
  • Build a LangChain agent that can interact with Bubble
  • 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 Bubble MCP server, and what's possible with it?

The Bubble MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bubble applications. It provides structured and secure access to your Bubble backend, so your agent can perform actions like creating and updating database entries, running workflows, fetching app data, and managing users on your behalf.

  • Automated database management: Your agent can create, update, or delete entries in your Bubble app’s database, streamlining data operations without manual input.
  • Workflow execution: Let your agent trigger workflows inside your Bubble app to automate complex business processes based on real-time prompts or events.
  • Dynamic data queries: Effortlessly ask your agent to fetch, filter, or search records from any data type within your Bubble app and return structured results.
  • User account administration: Enable your agent to create, update, or manage user profiles, permissions, and authentication flows directly in your Bubble environment.
  • App configuration and resource management: Allow your agent to adjust application settings, manage resources, or monitor usage metrics—keeping your Bubble project running smoothly.

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 Bubble 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 Bubble 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: ['bubble']
    }
);

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

Configure the agent with the MCP URL

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

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

Bulk Create Things

Tool to bulk create multiple Things in Bubble via newline-separated JSON.

Create Thing

Tool to create a new Thing.

Delete Thing By ID

Tool to delete a Bubble Thing by its unique ID.

Get Thing By ID

Retrieves a single Thing (record) from a Bubble Data Type by its unique ID.

Patch Thing By ID

Tool to modify selected fields on a Thing by its unique ID.

Replace Thing by ID

Tool to replace all editable fields on a Thing by its Unique ID.

Download File

Tool to download a file given its URL.

Create Temp File

Tool to upload bytes as a temporary file to Cloudflare R2 and return an S3 key.

Upload File

Tool to upload a file to Bubble storage.

Get Bubble API Swagger JSON

Tool to retrieve the auto-generated Swagger JSON for enabled APIs.

Get OAuth Access Token

Tool to exchange an authorization code or refresh token for an OAuth2 access token.

OAuth Authorize

Tool to initiate OAuth2 authorization flow for Bubble.

Bubble OAuth Register App

Tool to validate/initialize OAuth application credentials with Bubble.

Trigger Bubble Workflow via GET

Trigger a Bubble API workflow using an HTTP GET request.

Trigger Bubble Workflow via POST

Triggers a Bubble API workflow by name using a POST request.

FRAMEWORKS

How to build Bubble MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Bubble MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Bubble MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Bubble MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Bubble MCP with Claude Cowork

Codex logo

Codex

Use Bubble MCP with Codex

OpenClaw logo

OpenClaw

Use Bubble MCP with OpenClaw

Hermes logo

Hermes

Use Bubble MCP with Hermes

CLI logo

CLI

Use Bubble MCP with CLI

Google ADK logo

Google ADK

Use Bubble MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Bubble MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Bubble MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Bubble MCP with LlamaIndex

CrewAI logo

CrewAI

Use Bubble MCP with CrewAI

FAQ

Frequently asked questions

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

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

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A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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