FantasyData (SportsDataIO) 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 FantasyData (SportsDataIO) as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 FantasyData (SportsDataIO). "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in FantasyData (SportsDataIO)?"
)
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 FantasyData (SportsDataIO) MCP Server
Connect your FantasyData (SportsDataIO) account to any AI agent and take full control of your sports data analysis through natural conversation.
LlamaIndex agents combine FantasyData (SportsDataIO) 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
- NFL, NBA & MLB Player Intelligence — List all active players and fetch detailed profiles, positions, and statuses across major leagues
- Real-Time Score Tracking — Query live scores and game results for specific dates to stay updated on every match
- Schedule Navigation — Retrieve full schedules for upcoming seasons to plan your fantasy roster or betting strategies flawlessly
- Detailed Player Context — Resolve specific player IDs to get deep-dive metadata and performance background
- Multi-Sport Coverage — Unified access to football, basketball, and baseball data from a single integration
The FantasyData (SportsDataIO) 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 FantasyData (SportsDataIO) to LlamaIndex via MCP
Follow these steps to integrate the FantasyData (SportsDataIO) 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 FantasyData (SportsDataIO)
Why Use LlamaIndex with the FantasyData (SportsDataIO) MCP Server
LlamaIndex provides unique advantages when paired with FantasyData (SportsDataIO) through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine FantasyData (SportsDataIO) tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain FantasyData (SportsDataIO) tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query FantasyData (SportsDataIO), a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what FantasyData (SportsDataIO) tools were called, what data was returned, and how it influenced the final answer
FantasyData (SportsDataIO) + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the FantasyData (SportsDataIO) MCP Server delivers measurable value.
Hybrid search: combine FantasyData (SportsDataIO) real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query FantasyData (SportsDataIO) 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 FantasyData (SportsDataIO) for fresh data
Analytical workflows: chain FantasyData (SportsDataIO) queries with LlamaIndex's data connectors to build multi-source analytical reports
FantasyData (SportsDataIO) MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect FantasyData (SportsDataIO) to LlamaIndex via MCP:
get_mlb_player_details
Get details for a specific MLB player
get_mlb_schedule
Get the MLB schedule for a specific season
get_mlb_scores
Get MLB scores for a specific date
get_nba_player_details
Get details for a specific NBA player
get_nba_schedule
Get the NBA schedule for a specific season
get_nba_scores
Get NBA scores for a specific date
get_nfl_player_details
Get details for a specific NFL player
get_nfl_schedule
Get the NFL schedule for a specific season
get_nfl_scores
Get NFL scores for a specific date
list_mlb_players
List all active MLB players
list_nba_players
List all active NBA players
list_nfl_players
List all active NFL players
Example Prompts for FantasyData (SportsDataIO) in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with FantasyData (SportsDataIO) immediately.
"List all active NFL players."
"Show me the NBA scores for last night."
"Get the MLB schedule for the 2024 season."
Troubleshooting FantasyData (SportsDataIO) MCP Server with LlamaIndex
Common issues when connecting FantasyData (SportsDataIO) to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFantasyData (SportsDataIO) + LlamaIndex FAQ
Common questions about integrating FantasyData (SportsDataIO) 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 FantasyData (SportsDataIO) 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 FantasyData (SportsDataIO) to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.