How to integrate Brilliant directories MCP with CrewAI

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Introduction

This guide walks you through connecting Brilliant directories to CrewAI using the Composio tool router. By the end, you'll have a working Brilliant directories agent that can add a new member with company details, delete user and remove their uploaded images, list all categories used to organize members, show all available fields for user profiles through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Brilliant directories account through Composio's Brilliant directories 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 Brilliant directories connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Brilliant directories
  • Build a conversational loop where your agent can execute Brilliant directories 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 Brilliant directories MCP server, and what's possible with it?

The Brilliant directories MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Brilliant directories account. It provides structured and secure access to your membership community and business directory platform, so your agent can perform actions like managing users, retrieving data categories, and automating lead and review workflows on your behalf.

  • User creation and management: Easily instruct your agent to create new users with detailed profiles or delete existing members, streamlining your directory's onboarding and maintenance.
  • Deep data category access: Ask your agent to fetch all available data categories from your site, making it simple to organize content or power dynamic site navigation experiences.
  • Lead field discovery and automation: Let your agent retrieve the full structure of your leads table, helping you automate lead capture, validation, or enrichment workflows with up-to-date field metadata.
  • Review field extraction and insights: Direct your agent to pull all available review fields, enabling smarter review management, analytics, or custom reporting based on your site’s feedback system.
  • User data field exploration: Have your agent fetch and analyze all user-related fields, supporting advanced user segmentation, targeted updates, or personalized communications.

Supported Tools & Triggers

Tools
Create UserThis tool creates a new user record in the brilliant directories website database.
Delete UserThis tool deletes an existing user record from the brilliant directories website database.
Get Data CategoriesThis tool fetches all data categories in a brilliant directories website.
Get Lead FieldsThis tool retrieves all available fields in the leads table from a brilliant directories website.
Get Reviews FieldsThis tool retrieves all the available fields in the users reviews table from a brilliant directories website.
Get User FieldsThis tool fetches all available fields from the users data table in your brilliant directories website.

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 Brilliant directories 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 Brilliant directories 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 Brilliant directories MCP URL

Create a Composio Tool Router session for Brilliant directories

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["brilliant_directories"],
)
url = session.mcp.url
What's happening:
  • You create a Brilliant directories only session through Composio
  • Composio returns an MCP HTTP URL that exposes Brilliant directories 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="Brilliant directories Assistant",
    goal="Help users interact with Brilliant directories through natural language commands",
    backstory=(
        "You are an expert assistant with access to Brilliant directories tools. "
        "You can perform various Brilliant directories 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 Brilliant directories 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 Brilliant directories 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 Brilliant directories 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_brilliant_directories_agent.py

Complete Code

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

python
# file: crewai_brilliant_directories_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 Brilliant directories session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["brilliant_directories"],
    )
    url = session.mcp.url

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

    # Create Brilliant directories assistant agent
    toolkit_agent = Agent(
        role="Brilliant directories Assistant",
        goal="Help users interact with Brilliant directories through natural language commands",
        backstory=(
            "You are an expert assistant with access to Brilliant directories tools. "
            "You can perform various Brilliant directories 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 Brilliant directories 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 Brilliant directories 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 Brilliant directories through Composio's Tool Router. The agent can perform Brilliant directories 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 Brilliant directories MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

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Claude Agent SDK

Claude Agent SDK

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Google ADK

Google ADK

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LangChain

LangChain

Use Brilliant directories MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Brilliant directories MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Brilliant directories MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Brilliant directories MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Brilliant directories MCP?

With a standalone Brilliant directories MCP server, the agents and LLMs can only access a fixed set of Brilliant directories tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Brilliant directories 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 Brilliant directories tools.

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

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

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