How to Use the FanPower (PickUp) MCP in CrewAI

Q: How is fan prediction data secured during multi-agent CrewAI executions?

All tool calls to fetch fan predictions via listpicks run through secure, isolated HTTP transports. Agent memory is kept local to the execution run, ensuring sensitive fan choices are never leaked outside the secure MCP environment.

Run autonomous teams of specialized agents to manage FanPower (PickUp) game-day events, leaderboards, and rewards via CrewAI.

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Connect FanPower (PickUp) MCP to CrewAI

Create your Vinkius account to connect FanPower (PickUp) 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 FanPower (PickUp) with CrewAI

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Run autonomous game-day operations crews

Your moderator agent uses `list_events` to monitor active sports matches and identify when new interactive questions are needed. Simultaneously, a writer agent uses `list_questions` to review active prompts and drafts new ones based on live game events. This division of labor keeps your fan engagement fresh during fast-paced broadcasts. CrewAI manages the communication between these agents, ensuring they don't overwrite each other's work or double-post questions.

Analyze fan predictions using this MCP Server

An analyst agent calls `list_picks` to gather all fan predictions for a completed game. It then uses `get_pick_details` to analyze betting trends and identify which options attracted the most fan engagement. The agent packages these insights into a digest for your marketing team. Because CrewAI agents share memory, the analyst remembers previous game trends, allowing it to highlight shifting fan behaviors over time.

Audit leaderboard standing and prize distribution

A compliance agent uses `get_leaderboard` to verify the legitimacy of top-ranked fans before any prizes are handed out. It calls `get_fan_profile` to check for suspicious voting patterns or bot-like behavior. Once cleared, a fulfillment agent uses `get_reward_details` to select the correct prize from your catalog. Our MCP integration guarantees that compliance checks happen in real-time.

Setup guide

Set up FanPower (PickUp) 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 FanPower (PickUp) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent FanPower (PickUp) 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 FanPower (PickUp). 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 FanPower (PickUp) MCP in CrewAI

Pass the server URL to your agent's mcps configuration. You can use tool filters to give your analyst agent access to `list_picks` while restricting your compliance agent to `get_leaderboard` and `get_fan_profile`.

Yes. A customer service agent can fetch a fan's disputed pick via `get_pick_details`, while a supervisor agent checks their overall history using `get_fan_profile` to resolve the ticket autonomously.

CrewAI manages tool execution sequentially or hierarchically. This prevents your agents from spamming endpoints like `list_events` simultaneously, reducing the risk of API rate-limiting during live games.

Absolutely. You can run CrewAI in terminal environments to automate post-game audits. The crew boots up, calls `get_leaderboard` and `list_rewards`, updates your databases, and shuts down automatically.

All tool calls to fetch fan predictions via `list_picks` run through secure, isolated HTTP transports. Agent memory is kept local to the execution run, ensuring sensitive fan choices are never leaked outside the secure MCP environment.

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