How to integrate Botpress MCP with CrewAI

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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.

Supported Tools & Triggers

Tools
Break Down Workspace Usage By BotTool to break down workspace usage by bot.
BOTPRESS_CHARGE_WORKSPACE_UNPAID_INVOICESTool to charge unpaid invoices for a specific Botpress workspace.
Check Handle AvailabilityTool to check if a workspace handle is available in Botpress.
BOTPRESS_CREATE_ADMIN_INTEGRATIONTool to create a new integration in a Botpress workspace via the Admin API.
BOTPRESS_CREATE_ADMIN_WORKSPACETool to create a new workspace in Botpress via the Admin API.
BOTPRESS_CREATE_BOTTool to create a new bot in a Botpress workspace via the Admin API.
BOTPRESS_CREATE_CONVERSATIONTool to create a new conversation in Botpress via the Runtime API.
Delete Admin WorkspaceTool to permanently delete a workspace from Botpress admin.
Delete FilePermanently deletes a file from a Botpress bot's storage by its file ID.
Delete Integration Shareable IDTool to delete a shareable ID for an integration installed in a Botpress bot.
Delete Knowledge BasePermanently deletes a knowledge base from Botpress by its knowledge base ID.
Get AccountTool to get details of the authenticated account.
Get Account PreferenceTool to get a preference of the account.
Get All Workspace Quota CompletionTool to get a map of workspace IDs to their highest quota completion rate.
Get Dereferenced Public Plugin By IDTool to get a public plugin by ID with all interface entity references resolved to the corresponding entities as extended by the backing integrations.
Get IntegrationTool to get a specific Botpress integration by name and version.
Get Public IntegrationTool to retrieve a public integration by name and version from the Botpress hub.
Get Public Integration By IDTool to retrieve detailed information about a public Botpress integration by its ID.
Get Public InterfaceTool to get a public interface by name and version from the Botpress Hub.
Get Public Interface by IDTool to retrieve a public interface by its ID from the Botpress Hub.
Get Public PluginTool to retrieve detailed information about a public plugin from Botpress Hub by name and version.
Get Public Plugin By IDTool to retrieve details of a public plugin by its unique ID.
Get Public Plugin CodeTool to retrieve public plugin code from Botpress Hub.
Get Table RowTool to fetch a specific row from a table using the row's unique identifier.
Get Upcoming InvoiceTool to get the upcoming invoice for a workspace.
Get WorkspaceTool to get detailed information about a specific Botpress workspace by ID.
Get Workspace QuotaTool to get workspace quota information for a specific usage type.
LIST_ACTION_RUNSTool to list action runs for a specific integration of a bot.
LIST_BOT_ISSUESTool to list issues associated with a specific bot.
LIST_CONVERSATIONSTool to list all Conversations.
LIST_FILE_TAGSTool to list all tags used across all bot files.
LIST_FILE_TAG_VALUESTool to list all values for a given file tag across all files.
LIST_HUB_INTEGRATIONSTool to list public integrations from the Botpress hub.
LIST_INTEGRATION_API_KEYSTool to list Integration API Keys (IAKs) for a specific integration.
List IntegrationsTool to list integrations with filtering and sorting capabilities.
LIST_KNOWLEDGE_BASESTool to list knowledge bases for a bot.
List PluginsTool to list Botpress plugins.
List Public InterfacesTool to retrieve a list of public interfaces available in the Botpress Hub.
LIST_PUBLIC_PLUGINSTool to retrieve a list of public plugins available in the Botpress hub.
LIST_PUBLIC_WORKSPACESTool to retrieve a list of public workspaces.
LIST_USAGE_HISTORYTool to retrieve usage history for a bot or workspace.
List Workspace InvoicesTool to list all invoices billed to a workspace.
LIST_WORKSPACESList all Botpress workspaces accessible to the authenticated user.
Request Integration VerificationTool to request verification for a Botpress integration via the Admin API.
BOTPRESS_RUN_VRLTool to execute a VRL (Vector Remap Language) script against input data using the Botpress Admin API.
BOTPRESS_SEND_MESSAGETool to send a message to an existing Botpress conversation via the Runtime API.
Set Account PreferenceTool to set a preference for the account.
Set Workspace PreferenceTool to set a preference for a Botpress workspace.
Update AccountTool to update details of the authenticated account.
BOTPRESS_UPDATE_ADMIN_BOTSTool to update an existing bot in a Botpress workspace via the Admin API.
UPDATE_ADMIN_WORKSPACETool to update a Botpress workspace via the Admin API.
BOTPRESS_UPDATE_WORKFLOWTool to update a workflow object in Botpress by setting parameter values.
BOTPRESS_VALIDATE_INTEGRATION_UPDATETool to validate an integration update request in Botpress Admin API.

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

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

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.

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

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

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

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

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.

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

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FAQ

What are the differences in Tool Router MCP and Botpress MCP?

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.

Can I use Tool Router MCP with CrewAI?

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.

Can I manage the permissions and scopes for Botpress while using Tool Router?

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.

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 Botpress data and credentials are handled as safely as possible.

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