FanPower (PickUp) MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add FanPower (PickUp) as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to FanPower (PickUp). "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in FanPower (PickUp)?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About FanPower (PickUp) MCP Server
Connect your FanPower (now PickUp) engagement account to any AI agent and take full control of your interactive sports and esports content through natural conversation.
LlamaIndex agents combine FanPower (PickUp) tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Interactive Content Management — List all engagement questions and fetch detailed configurations for your interactive widgets
- Fan Pick Tracking — List and inspect individual fan answers (picks) to understand audience predictions and sentiment
- Audience Profiling — Retrieve fan profiles and participation history to build your zero-party database
- Gamification & Rewards — Monitor available rewards, achievements, and leaderboard rankings natively
- Event Coordination — List and inspect sports/esports events associated with your interactive content
- Identity Context — Verify your API user profile and authorized access levels flawlessly
The FanPower (PickUp) MCP Server exposes 12 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect FanPower (PickUp) to LlamaIndex via MCP
Follow these steps to integrate the FanPower (PickUp) MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 12 tools from FanPower (PickUp)
Why Use LlamaIndex with the FanPower (PickUp) MCP Server
LlamaIndex provides unique advantages when paired with FanPower (PickUp) through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine FanPower (PickUp) tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain FanPower (PickUp) tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query FanPower (PickUp), a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what FanPower (PickUp) tools were called, what data was returned, and how it influenced the final answer
FanPower (PickUp) + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the FanPower (PickUp) MCP Server delivers measurable value.
Hybrid search: combine FanPower (PickUp) real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query FanPower (PickUp) to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying FanPower (PickUp) for fresh data
Analytical workflows: chain FanPower (PickUp) queries with LlamaIndex's data connectors to build multi-source analytical reports
FanPower (PickUp) MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect FanPower (PickUp) to LlamaIndex via MCP:
get_event_details
Get details for a specific event
get_fan_profile
Get the profile of a specific fan
get_leaderboard
Get the fan leaderboard for engagement scores
get_me
Get current API user identity
get_pick_details
Get details for a specific fan pick
get_question
Get details for a specific engagement question
get_reward_details
Get details for a specific reward
list_events
List sports or esports events with interactive content
list_fans
List registered fans and participants
list_picks
List fan picks (answers) for interactive content
list_questions
List all interactive fan engagement questions
list_rewards
List available rewards and achievements
Example Prompts for FanPower (PickUp) in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with FanPower (PickUp) immediately.
"List all active engagement questions on FanPower."
"Show me the top 5 fans on the leaderboard."
"List the latest fan picks for the Lakers vs Celtics game."
Troubleshooting FanPower (PickUp) MCP Server with LlamaIndex
Common issues when connecting FanPower (PickUp) to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFanPower (PickUp) + LlamaIndex FAQ
Common questions about integrating FanPower (PickUp) MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect FanPower (PickUp) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect FanPower (PickUp) to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.