How to Use the AdsWizz MCP in CrewAI

Q: How can I set up a CrewAI team to analyze my AdsWizz ad performance?

Create a Reporter agent that uses the getaudioperformance tool and an Analyst agent to process the results. The first agent gathers the raw data from AdsWizz, and the second finds insights.

Deploy a crew of AI agents to autonomously manage your AdsWizz audio advertising operations with CrewAI.

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Connect AdsWizz MCP to CrewAI

Create your Vinkius account to connect AdsWizz to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup AdsWizz with CrewAI

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Assemble a Performance Analysis Crew

Assign a 'Reporter' agent to pull weekly metrics using `get_audio_performance`. Then, have an 'Analyst' agent take that data, look for trends or anomalies, and summarize its findings. This divides the labor for better results. CrewAI's shared memory means the Analyst agent gets the exact data the Reporter agent fetched. This setup lets you build a team that handles the entire reporting pipeline, from data fetching to insight generation, all on its own.

Build an Autonomous Campaign Management Team

Create a 'Campaign Monitor' agent that uses `list_campaigns` to watch for newly created campaigns. When it finds one, it passes the ID to a 'Validator' agent, which uses `get_campaign` to check its configuration against a set of predefined rules. This is how you build autonomous oversight for your AdsWizz account. The crew works 24/7, ensuring new campaigns stick to your guidelines without a human having to manually check each one. This is what an autonomous MCP Server workflow looks like.

Deploy an Inventory Scout Agent

Deploy a 'Scout' agent whose only job is to watch advertising inventory. It uses `list_zones` to get a constant read on available podcasts and streams. If new, high-value inventory appears, it can flag it for your ad-ops team. You can make this even smarter with a second 'Strategist' agent. The Scout finds inventory, and the Strategist checks if it aligns with any current campaign goals. This is role-based specialization in action.

Setup guide

Set up AdsWizz MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke AdsWizz tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="AdsWizz Analyst",
    goal="Access and analyze AdsWizz data via MCP.",
    backstory="Expert analyst with direct AdsWizz access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent AdsWizz transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="AdsWizz Analyst",
        goal="Access and analyze AdsWizz data via MCP.",
        backstory="Expert analyst with direct AdsWizz access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent AdsWizz transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AdsWizz. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about AdsWizz MCP in CrewAI

Create a Reporter agent that uses the `get_audio_performance` tool and an Analyst agent to process the results. The first agent gathers the raw data from AdsWizz, and the second finds insights.

Yes, that's a perfect use case. Set up one agent to find new campaigns with `list_campaigns`, and a second 'Validator' agent to check them using `get_campaign` against your rules.

Specialization. You can have one agent for data gathering, another for analysis, and a third for taking action. It's more organized and powerful than one agent trying to do everything.

It's one line of code. You just pass your Vinkius URL into the `mcps` parameter when you define your Agent in CrewAI. The framework handles the connection and tool setup.

The agents will only touch your AdsWizz campaign data and ad performance statistics. Each tool call is authenticated with your private token and executed inside a V8 Isolate Sandbox on Vinkius, which is destroyed after the task is complete.

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