How to Use the AdButler MCP in CrewAI

Q: How do I assign specific AdButler tools to a single agent in CrewAI?

Use the toolfilter option in MCPServerHTTP to restrict tools. You can assign getstats to your analyst agent while keeping other tools hidden.

Q: How do I connect my CrewAI agents to the AdButler MCP Server?

Add your Vinkius endpoint URL directly to the mcps array in your Agent definition. CrewAI handles the connection and exposes the tools automatically.

Run specialized multi-agent teams with CrewAI to audit, optimize, and report on your AdButler campaigns.

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Connect AdButler MCP to CrewAI

Create your Vinkius account to connect AdButler 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 AdButler with CrewAI

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Perplexity

Collaborative AdButler audits with CrewAI

The `get_stats` and `list_banners` tools extract live impression counts and active creatives. Assign one agent to act as your Ad Analyst and another as your Campaign Auditor. The analyst tracks impressions while the auditor uses `get_campaign` to verify creative alignment. By sharing memory and context, the agents collaborate to find underperforming banners and suggest layout improvements without manual intervention.

Restricting AdButler tools in this MCP Server

The `list_placements` and `list_zones` tools expose your targeting layout and zone structures. Do not let every agent in your crew access your entire ad network. Use `MCPServerHTTP` from `crewai.mcp` along with `tool_filter` to expose only what each agent needs. Your reporting agent only gets performance statistics, while your setup agent gets layout details, minimizing security risks.

Hierarchical campaign optimization

The `check_adbutler_status` and `list_advertisers` tools verify your connection and retrieve account structures. Run your crew under a manager agent that directs the workflow. The manager delegates tasks to check API health, fetch advertiser details, and compile publisher lists with `list_publishers`. This structured execution path ensures that data is collected, reviewed, and formatted in a reliable, repeatable sequence.

Setup guide

Set up AdButler 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 AdButler tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent AdButler 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="AdButler Analyst",
        goal="Access and analyze AdButler data via MCP.",
        backstory="Expert analyst with direct AdButler access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent AdButler 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 AdButler. 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 AdButler MCP in CrewAI

Use the `tool_filter` option in `MCPServerHTTP` to restrict tools. You can assign `get_stats` to your analyst agent while keeping other tools hidden.

Yes, by setting up a sequential workflow. One agent fetches active assets via `list_banners`, and the next agent analyzes their performance metrics using `get_stats`.

Add your Vinkius endpoint URL directly to the `mcps` array in your Agent definition. CrewAI handles the connection and exposes the tools automatically.

CrewAI supports stdio, SSE, and Streamable HTTP transports, letting you connect to your hosted Vinkius endpoint using whichever method fits your network architecture.

All campaign data, banner links, and publisher records are processed inside Vinkius's secure, ephemeral V8 isolates. No data persists once your crew completes its execution.

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