How to integrate Botpress MCP with LangChain

This guide walks you through connecting Botpress to LangChain using the Composio tool router. By the end, you'll have a working Botpress agent that can list all active conversations for your bot, show issues reported for a specific bot, delete a file from a bot workspace through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Botpress account through Composio's Botpress MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Botpress is an open-source platform for building, deploying, and managing chatbots. It helps teams automate conversations and deliver rich, interactive messaging experiences.

53 Tools

Introduction

This guide walks you through connecting Botpress to LangChain using the Composio tool router. By the end, you'll have a working Botpress agent that can list all active conversations for your bot, show issues reported for a specific bot, delete a file from a bot workspace through natural language commands.

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

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

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

The Botpress MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Botpress account. It provides structured and secure access to your chatbot platform, so your agent can perform actions like listing conversations, managing bot files, tracking issues, and exploring workspaces on your behalf.

  • Comprehensive conversation management: Retrieve and paginate through all chatbot conversations, making it easy to review chat history and analyze user interactions.
  • Bot issue tracking and diagnostics: List and investigate issues related to specific bots, helping you stay informed about errors or configuration problems as they arise.
  • Workspace discovery and organization: Browse both public and private workspaces, making it seamless to manage your bot environments or explore new collaborative spaces.
  • File and tag oversight: List, manage, and categorize bot files and their associated tags or tag values, streamlining bot asset organization.
  • Account information access: Instantly fetch authenticated account details so your agent always works with the latest profile and permission data.

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 Botpress 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 Botpress 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: ['botpress']
    }
);

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

Configure the agent with the MCP URL

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

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

Break Down Workspace Usage By Bot

Tool to break down workspace usage by bot.

BOTPRESS_CHARGE_WORKSPACE_UNPAID_INVOICES

Tool to charge unpaid invoices for a specific Botpress workspace.

Check Handle Availability

Tool to check if a workspace handle is available in Botpress.

BOTPRESS_CREATE_ADMIN_INTEGRATION

Tool to create a new integration in a Botpress workspace via the Admin API.

BOTPRESS_CREATE_ADMIN_WORKSPACE

Tool to create a new workspace in Botpress via the Admin API.

BOTPRESS_CREATE_BOT

Tool to create a new bot in a Botpress workspace via the Admin API.

BOTPRESS_CREATE_CONVERSATION

Tool to create a new conversation in Botpress via the Runtime API.

Delete Admin Workspace

Tool to permanently delete a workspace from Botpress admin.

Delete File

Permanently deletes a file from a Botpress bot's storage by its file ID.

Delete Integration Shareable ID

Tool to delete a shareable ID for an integration installed in a Botpress bot.

Delete Knowledge Base

Permanently deletes a knowledge base from Botpress by its knowledge base ID.

Get Account

Tool to get details of the authenticated account.

Get Account Preference

Tool to get a preference of the account.

Get All Workspace Quota Completion

Tool to get a map of workspace IDs to their highest quota completion rate.

Get Dereferenced Public Plugin By ID

Tool to get a public plugin by ID with all interface entity references resolved to the corresponding entities as extended by the backing integrations.

Get Integration

Tool to get a specific Botpress integration by name and version.

Get Public Integration

Tool to retrieve a public integration by name and version from the Botpress hub.

Get Public Integration By ID

Tool to retrieve detailed information about a public Botpress integration by its ID.

Get Public Interface

Tool to get a public interface by name and version from the Botpress Hub.

Get Public Interface by ID

Tool to retrieve a public interface by its ID from the Botpress Hub.

Get Public Plugin

Tool to retrieve detailed information about a public plugin from Botpress Hub by name and version.

Get Public Plugin By ID

Tool to retrieve details of a public plugin by its unique ID.

Get Public Plugin Code

Tool to retrieve public plugin code from Botpress Hub.

Get Table Row

Tool to fetch a specific row from a table using the row's unique identifier.

Get Upcoming Invoice

Tool to get the upcoming invoice for a workspace.

Get Workspace

Tool to get detailed information about a specific Botpress workspace by ID.

Get Workspace Quota

Tool to get workspace quota information for a specific usage type.

LIST_ACTION_RUNS

Tool to list action runs for a specific integration of a bot.

LIST_BOT_ISSUES

Tool to list issues associated with a specific bot.

LIST_CONVERSATIONS

Tool to list all Conversations.

LIST_FILE_TAGS

Tool to list all tags used across all bot files.

LIST_FILE_TAG_VALUES

Tool to list all values for a given file tag across all files.

LIST_HUB_INTEGRATIONS

Tool to list public integrations from the Botpress hub.

LIST_INTEGRATION_API_KEYS

Tool to list Integration API Keys (IAKs) for a specific integration.

List Integrations

Tool to list integrations with filtering and sorting capabilities.

LIST_KNOWLEDGE_BASES

Tool to list knowledge bases for a bot.

List Plugins

Tool to list Botpress plugins.

List Public Interfaces

Tool to retrieve a list of public interfaces available in the Botpress Hub.

LIST_PUBLIC_PLUGINS

Tool to retrieve a list of public plugins available in the Botpress hub.

LIST_PUBLIC_WORKSPACES

Tool to retrieve a list of public workspaces.

LIST_USAGE_HISTORY

Tool to retrieve usage history for a bot or workspace.

List Workspace Invoices

Tool to list all invoices billed to a workspace.

LIST_WORKSPACES

List all Botpress workspaces accessible to the authenticated user.

Request Integration Verification

Tool to request verification for a Botpress integration via the Admin API.

BOTPRESS_RUN_VRL

Tool to execute a VRL (Vector Remap Language) script against input data using the Botpress Admin API.

BOTPRESS_SEND_MESSAGE

Tool to send a message to an existing Botpress conversation via the Runtime API.

Set Account Preference

Tool to set a preference for the account.

Set Workspace Preference

Tool to set a preference for a Botpress workspace.

Update Account

Tool to update details of the authenticated account.

BOTPRESS_UPDATE_ADMIN_BOTS

Tool to update an existing bot in a Botpress workspace via the Admin API.

UPDATE_ADMIN_WORKSPACE

Tool to update a Botpress workspace via the Admin API.

BOTPRESS_UPDATE_WORKFLOW

Tool to update a workflow object in Botpress by setting parameter values.

BOTPRESS_VALIDATE_INTEGRATION_UPDATE

Tool to validate an integration update request in Botpress Admin API.

FRAMEWORKS

How to build Botpress MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Botpress MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Botpress MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Botpress MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Botpress MCP with Claude Cowork

Codex logo

Codex

Use Botpress MCP with Codex

OpenClaw logo

OpenClaw

Use Botpress MCP with OpenClaw

Hermes logo

Hermes

Use Botpress MCP with Hermes

CLI logo

CLI

Use Botpress MCP with CLI

Google ADK logo

Google ADK

Use Botpress MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Botpress MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Botpress MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Botpress MCP with LlamaIndex

CrewAI logo

CrewAI

Use Botpress MCP with CrewAI

FAQ

Frequently asked questions

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

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

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

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Co-founder, Slashy

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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Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

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CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

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Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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Co-Founder, Ingram Technologies