How to integrate Botpress MCP with Autogen

This guide walks you through connecting Botpress to AutoGen 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 AutoGen 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 AutoGen 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 AutoGen 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

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Botpress
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Botpress tools
  • Run a live chat loop where you ask the agent to perform Botpress operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Botpress account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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 python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Botpress via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Botpress connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Botpress session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["botpress"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Botpress tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Botpress assistant agent with MCP tools
    agent = AssistantAgent(
        name="botpress_assistant",
        description="An AI assistant that helps with Botpress operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Botpress tools from the workbench
8

Run the interactive chat loop

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

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

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

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Botpress tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

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

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Botpress session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["botpress"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Botpress assistant agent with MCP tools
        agent = AssistantAgent(
            name="botpress_assistant",
            description="An AI assistant that helps with Botpress operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

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

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

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

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into Botpress through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Botpress, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
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

LangChain logo

LangChain

Use Botpress MCP with LangChain

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. Autogen 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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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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Co-founder, Opennote

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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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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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