# How to integrate Adyntel MCP with CrewAI

```json
{
  "title": "How to integrate Adyntel MCP with CrewAI",
  "toolkit": "Adyntel",
  "toolkit_slug": "adyntel",
  "framework": "CrewAI",
  "framework_slug": "crew-ai",
  "url": "https://composio.dev/toolkits/adyntel/framework/crew-ai",
  "markdown_url": "https://composio.dev/toolkits/adyntel/framework/crew-ai.md",
  "updated_at": "2026-05-06T07:59:21.684Z"
}
```

## Introduction

This guide walks you through connecting Adyntel to CrewAI using the Composio tool router. By the end, you'll have a working Adyntel agent that can find linkedin ads for nike.com, show all google ads for amazon.com, search meta ads for fitness trackers through natural language commands.
This guide will help you understand how to give your CrewAI agent real control over a Adyntel account through Composio's Adyntel MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Adyntel with

- [OpenAI Agents SDK](https://composio.dev/toolkits/adyntel/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/adyntel/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/adyntel/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/adyntel/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/adyntel/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/adyntel/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/adyntel/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/adyntel/framework/cli)
- [Google ADK](https://composio.dev/toolkits/adyntel/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/adyntel/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/adyntel/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/adyntel/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/adyntel/framework/llama-index)

## TL;DR

Here's what you'll learn:
- Get a Composio API key and configure your Adyntel connection
- Set up CrewAI with an MCP enabled agent
- Create a Tool Router session or standalone MCP server for Adyntel
- Build a conversational loop where your agent can execute Adyntel 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 Adyntel MCP server, and what's possible with it?

The Adyntel MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Adyntel account. It provides structured and secure access to company ad intelligence, so your agent can retrieve LinkedIn, Google, Meta, and TikTok ads, analyze campaign performance, and surface competitive ad insights on your behalf.
- Company-specific ad retrieval: Instantly fetch all Google ads associated with any company's domain for in-depth competitive analysis.
- Meta ad library search: Direct your agent to explore Meta's ad archive, surfacing ads by keyword, brand, or campaign theme.
- TikTok ad discovery: Search and analyze TikTok ads using targeted keywords to identify creative trends and campaign strategies.
- Cross-platform ad intelligence: Aggregate and compare ad content and strategies across platforms for a unified marketing view.
- Competitive campaign benchmarking: Let your agent compile and summarize ad performance data to benchmark competitors and inform your own ad strategy.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ADYNTEL_GET_GOOGLE_ADS_BY_COMPANY` | Get Google Ads By Company | Retrieve all google ads for a given company domain. |
| `ADYNTEL_META_AD_SEARCH` | Search Meta Ads | Search the meta ad library. |
| `ADYNTEL_SEARCH_TIK_TOK_ADS` | Search TikTok Ads | Tool to search for ads on tiktok using a keyword. use when you want to find ads related to a specific topic. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Adyntel MCP server is an implementation of the Model Context Protocol that connects your AI agent to Adyntel. It provides structured and secure access so your agent can perform Adyntel operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Python 3.9 or higher
- A Composio account and API key
- A Adyntel connection authorized in Composio
- An OpenAI API key for the CrewAI LLM
- Basic familiarity with Python

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

**What's happening:**
- composio connects your agent to Adyntel via MCP
- crewai provides Agent, Task, Crew, and LLM primitives
- crewai-tools[mcp] includes MCP helpers
- python-dotenv loads environment variables from .env
```bash
pip install composio crewai crewai-tools[mcp] python-dotenv
```

### 3. Set up environment variables

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
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

**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 Adyntel MCP URL
```python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
```

### 5. Create a Composio Tool Router session for Adyntel

**What's happening:**
- You create a Adyntel only session through Composio
- Composio returns an MCP HTTP URL that exposes Adyntel tools
```python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["adyntel"])

url = session.mcp.url
```

### 6. Initialize the MCP Server

**What's Happening:**
- Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
- MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
- Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
- Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
- Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
```python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
```

### 7. Create a CLI Chatloop and define the Crew

**What's Happening:**
- Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
- Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
- Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
- Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
- Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
- Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.
```python
print("Chat started! Type 'exit' or 'quit' to end.\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"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

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

## Complete Code

```python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["adyntel"],
)
url = session.mcp.url

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

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\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"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

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

## Conclusion

You now have a CrewAI agent connected to Adyntel through Composio's Tool Router. The agent can perform Adyntel 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 Adyntel MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/adyntel/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/adyntel/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/adyntel/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/adyntel/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/adyntel/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/adyntel/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/adyntel/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/adyntel/framework/cli)
- [Google ADK](https://composio.dev/toolkits/adyntel/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/adyntel/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/adyntel/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/adyntel/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/adyntel/framework/llama-index)

## Related Toolkits

- [Metaads](https://composio.dev/toolkits/metaads) - Metaads is Meta's official Ads API that lets you manage, analyze, and optimize your Facebook and Instagram ad campaigns. Streamline ad operations and gain deeper insights with robust automation.
- [Adrapid](https://composio.dev/toolkits/adrapid) - Adrapid is a platform for rapid creation of digital marketing visuals using templates. It streamlines design workflows for banners, images, and HTML5 content with automation.
- [Beaconstac](https://composio.dev/toolkits/beaconstac) - Beaconstac is a platform for creating and managing QR codes and proximity beacons. It helps businesses engage customers and track marketing performance with powerful analytics.
- [Campaign cleaner](https://composio.dev/toolkits/campaign_cleaner) - Campaign cleaner is an email campaign optimization tool that boosts compatibility and deliverability across email clients. It helps marketers get better results by cleaning, enhancing, and ensuring high performance for every campaign.
- [Deadline funnel](https://composio.dev/toolkits/deadline_funnel) - Deadline Funnel lets you create personalized deadlines and timers for your marketing campaigns. It helps marketers boost conversions by adding authentic urgency to offers.
- [Google Ads](https://composio.dev/toolkits/googleads) - Google Ads is Google's online advertising platform for creating, managing, and optimizing digital campaigns. It helps businesses reach targeted customers and maximize return on ad spend.
- [Instantly](https://composio.dev/toolkits/instantly) - Instantly is a platform for automating cold email outreach, managing leads, and optimizing deliverability. Get better results from email campaigns with minimal manual effort.
- [Proofly](https://composio.dev/toolkits/proofly) - Proofly is a social proof platform that displays real-time notifications of customer activity on your site. It helps you increase website conversions by building trust and urgency for visitors.
- [Segmetrics](https://composio.dev/toolkits/segmetrics) - Segmetrics is a marketing analytics platform that reveals detailed insights into your customer journeys. It helps businesses optimize marketing strategies with accurate, actionable reporting.
- [Semrush](https://composio.dev/toolkits/semrush) - Semrush is a leading SEO tool suite for keyword research, competitor analysis, and campaign tracking. It empowers marketers to improve search rankings and optimize online visibility.
- [Sendloop](https://composio.dev/toolkits/sendloop) - Sendloop is an all-in-one email marketing platform built for SaaS, e-commerce, and small businesses. It makes it easy to send campaigns, manage lists, and track results—all in one place.
- [Sidetracker](https://composio.dev/toolkits/sidetracker) - Sidetracker is a marketing analytics platform that tracks expenses, sales funnels, and customer journeys. It helps optimize marketing spend and visualize campaign performance from start to finish.
- [Stannp](https://composio.dev/toolkits/stannp) - Stannp is an API-driven direct mail platform for sending postcards and letters programmatically. It lets you automate physical mail delivery—no manual printing or mailing required.
- [Tapfiliate](https://composio.dev/toolkits/tapfiliate) - Tapfiliate is an affiliate and referral tracking platform for businesses. It helps companies efficiently manage, track, and grow their affiliate programs.
- [Tpscheck](https://composio.dev/toolkits/tpscheck) - Tpscheck is a real-time service for verifying UK phone numbers against TPS and CTPS registers. It helps prevent unwanted marketing calls and ensures compliance with UK telemarketing laws.
- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options.
- [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.
- [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.
- [Twitter](https://composio.dev/toolkits/twitter) - Twitter is a social media platform for sharing real-time updates, conversations, and news. Stay connected, informed, and engaged with communities worldwide.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Adyntel MCP?

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

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

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
