How to integrate Botpress MCP with CrewAI

This guide walks you through connecting Botpress to CrewAI 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 CrewAI 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.

Botpress logoBotpress
Api Key

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 CrewAI 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 CrewAI 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.

Also integrate Botpress with

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Botpress connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Botpress
  • Build a conversational loop where your agent can execute Botpress operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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 step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Botpress connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
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

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Botpress via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_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 with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
5

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Botpress MCP URL
6

Create a Composio Tool Router session for Botpress

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["botpress"])

url = session.mcp.url
What's happening:
  • You create a Botpress only session through Composio
  • Composio returns an MCP HTTP URL that exposes Botpress tools
7

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
8

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Botpress and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["botpress"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Botpress through Composio's Tool Router. The agent can perform Botpress operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations
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.

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. CrewAI 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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