How to integrate Beaconstac MCP with Autogen

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Introduction

This guide walks you through connecting Beaconstac to AutoGen using the Composio tool router. By the end, you'll have a working Beaconstac agent that can create a qr code template for event tickets, list all physical places registered for my brand, delete an outdated qr code template, organize qr codes using a new tag through natural language commands.

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

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

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 Beaconstac
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Beaconstac tools
  • Run a live chat loop where you ask the agent to perform Beaconstac 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 Beaconstac MCP server, and what's possible with it?

The Beaconstac MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Beaconstac account. It provides structured and secure access to your QR code and proximity marketing assets, so your agent can perform actions like creating QR templates, managing places and tags, and organizing collections on your behalf.

  • QR code template creation and management: Easily instruct your agent to create new QR code templates or delete outdated ones, streamlining your marketing campaigns.
  • Place and location asset organization: Let your agent register new places or list all your locations for precise proximity marketing management.
  • Bulk QR code collection browsing: Have your agent search, filter, and organize your bulk QR code collections to keep assets accessible and sorted.
  • Tagging and categorization automation: Direct your agent to create or delete tags, making it simple to categorize and organize QR codes and related objects.
  • Organization and user management: Enable your agent to list organizations, onboard new users, or manage access for streamlined account administration.

Supported Tools & Triggers

Tools
Create PlaceTool to create a new place for location-based assets.
Create QR TemplateTool to create a new qr code template.
Create TagTool to create a new tag for organizing qr codes and other objects.
Create UserTool to create a new user.
Delete QR CodeTool to delete a qr code by its id.
Delete QR Code TemplateTool to delete a qr code template by its id.
Delete TagTool to delete a tag by its id.
List Bulk QR Code CollectionsTool to list bulk qr code collections.
List OrganizationsTool to list organizations.
List PlacesTool to list your places.
List QR TemplatesTool to list all qr code templates in your account.
List TagsTool to list all tags with optional filtering and pagination.
List UsersTool to list all users with optional filtering, searching, ordering, and pagination.
Get Period OverviewTool to get period overview analytics for products including counts, impressions, and conversion percentage.
Get Product OverviewTool to get analytics overview for a specified product type over a given time interval.
Retrieve QR CodeTool to retrieve details of a specific qr code by its id.
Retrieve UserTool to retrieve the details of an existing user by id.
Update PlaceTool to update the specified place by id.
Update QR CodeTool to update an existing qr code by its id.
Update TagTool to update an existing tag by its id.
Update UserTool to update an existing user.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Beaconstac account you can connect to Composio
  • Some basic familiarity with Autogen and Python async

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 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 Beaconstac via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

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 Beaconstac connections to use

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 Beaconstac session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["beaconstac"]
    )
    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 Beaconstac tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to

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

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 Beaconstac assistant agent with MCP tools
    agent = AssistantAgent(
        name="beaconstac_assistant",
        description="An AI assistant that helps with Beaconstac 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 Beaconstac tools from the workbench

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Beaconstac 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 Beaconstac 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 Beaconstac 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 Beaconstac session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["beaconstac"]
    )
    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 Beaconstac assistant agent with MCP tools
        agent = AssistantAgent(
            name="beaconstac_assistant",
            description="An AI assistant that helps with Beaconstac 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 Beaconstac 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 Beaconstac 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 Beaconstac, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build Beaconstac MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Beaconstac MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Beaconstac MCP with Claude Agent SDK

Google ADK

Google ADK

Use Beaconstac MCP with Google ADK

LangChain

LangChain

Use Beaconstac MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Beaconstac MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Beaconstac MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Beaconstac MCP with LlamaIndex

CrewAI

CrewAI

Use Beaconstac MCP with CrewAI

FAQ

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

With a standalone Beaconstac MCP server, the agents and LLMs can only access a fixed set of Beaconstac tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Beaconstac and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with Autogen?

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 Beaconstac tools.

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

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

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