How to integrate Metaads MCP with CrewAI

BOOK A CALLGET STARTED FOR FREE
Framework Integration Gradient
Metaads Logo
CrewAI Logo
divider

Introduction

This guide walks you through connecting Metaads to CrewAI using the Composio tool router. By the end, you'll have a working Metaads agent that can get ad performance insights for last week, create a new campaign for summer sale, pause all ads in underperforming campaigns, build a custom audience from website visitors through natural language commands.

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

The Metaads MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Meta Ads account. It provides structured and secure access to your advertising assets, so your agent can perform actions like creating campaigns, managing ads, analyzing insights, and handling audiences on your behalf.

  • Automated campaign and ad creation: Quickly launch new campaigns, ad sets, and ads—including image, video, carousel, and collection formats—without manual setup.
  • Real-time ad performance insights: Instantly retrieve analytics and detailed insights for any ad account, campaign, ad set, or individual ad to monitor and optimize your strategies.
  • Audience management and targeting: Effortlessly create and update custom audiences, from customer lists to website visitors, so your ads reach the right people.
  • Campaign control and optimization: Pause or delete campaigns and creatives, allowing your agent to manage spend and keep your advertising up to date.
  • Creative asset automation: Generate, fetch, or remove ad creatives on the fly, making it easy to test new visuals or messaging across your campaigns.

Supported Tools & Triggers

Tools
Create AdCreate a new ad within an ad set using the meta marketing api.
Create Ad CreativeCreate a new ad creative using the meta marketing api.
Create Ad SetCreate a new ad set within a campaign using the meta marketing api.
Create CampaignCreate a new advertising campaign using the meta marketing api.
Create Custom AudienceCreate a new custom audience using the meta marketing api.
Delete Ad CreativeDelete ad creative
Delete CampaignDelete an advertising campaign using the meta marketing api.
Get Ad CreativeGet ad creative
Get InsightsGet insights data for a meta ads object (ad account, campaign, ad set, or ad) using the meta marketing api.
Pause CampaignPause an advertising campaign using the meta marketing api.
Preview Ad CreativePreview ad creative
Read Ad SetsRetrieve ad sets from a meta ad account using the marketing api.
Resume CampaignResume a paused advertising campaign using the meta marketing api.
Update Ad CreativeUpdate ad creative
Update CampaignUpdate an existing advertising campaign using the meta marketing api.
Upload Ad ImageUpload an image for use in meta ad creatives using the marketing api.

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 Metaads 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 Metaads 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 Metaads MCP URL

Create a Composio Tool Router session for Metaads

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

Complete Code

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

python
# file: crewai_metaads_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 Metaads session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["metaads"],
    )
    url = session.mcp.url

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

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

OpenAI Agents SDK

OpenAI Agents SDK

Use Metaads MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Metaads MCP with Claude Agent SDK

Google ADK

Google ADK

Use Metaads MCP with Google ADK

LangChain

LangChain

Use Metaads MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Metaads MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Metaads MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Metaads MCP with LlamaIndex

FAQ

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

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

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

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

Used by agents from

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

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Book a call↗Get started for free