How to integrate Botpress MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Botpress to the OpenAI Agents SDK 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 OpenAI Agents SDK 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 and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Botpress
  • Configure an AI agent that can use Botpress as a tool
  • Run a live chat session where you can ask the agent to perform Botpress operations

What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Botpress project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Botpress.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Botpress Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["botpress"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only botpress.
  • The router checks the user's Botpress connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Botpress.
  • This approach keeps things lightweight and lets the agent request Botpress tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Botpress. "
        "Help users perform Botpress operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Botpress and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Botpress operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Botpress.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Botpress and OpenAI Agents SDK:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["botpress"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Botpress. "
        "Help users perform Botpress operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Botpress MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Botpress.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

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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 OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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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