How to integrate Beaconstac MCP with CrewAI

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Introduction

This guide walks you through connecting Beaconstac to CrewAI 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agent that can create a qr code template for event tickets, list all physical places registered for my brand, delete an outdated qr code template, organize qr codes using a new tag through natural language commands.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 CrewAI 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 a Composio API key and configure your Beaconstac connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Beaconstac
  • Build a conversational loop where your agent can execute Beaconstac 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 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  • QR code template creation and management: Easily instruct your agent to create new QR code templates or delete outdated ones, streamlining your marketing campaigns.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

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Beaconstac 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 python-dotenv
What's happening:
  • composio connects your agent to Beaconstac via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools 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
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
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 Beaconstac MCP URL

Create a Composio Tool Router session for Beaconstac

python
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:
  • You create a Beaconstac only session through Composio
  • Composio returns an MCP HTTP URL that exposes Beaconstac tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Beaconstac Assistant",
    goal="Help users interact with Beaconstac through natural language commands",
    backstory=(
        "You are an expert assistant with access to Beaconstac tools. "
        "You can perform various Beaconstac operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Beaconstac MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Beaconstac operations.\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"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Beaconstac related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_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:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_beaconstac_agent.py

Complete Code

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

python
# file: crewai_beaconstac_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

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

    # Create Beaconstac assistant agent
    toolkit_agent = Agent(
        role="Beaconstac Assistant",
        goal="Help users interact with Beaconstac through natural language commands",
        backstory=(
            "You are an expert assistant with access to Beaconstac tools. "
            "You can perform various Beaconstac operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Beaconstac operations.\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"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Beaconstac related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

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

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Beaconstac through Composio's Tool Router. The agent can perform Beaconstac 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

How to build Beaconstac MCP Agent with another framework

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 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 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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ASU
Letta
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HubSpot
Agent.ai
Altera
DataStax
Entelligence
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Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

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