How to Use the Broadage Sports MCP in LlamaIndex

Q: How do I filter specific tournaments during the indexing process?

You use the allowedtools filter when setting up your tool specification. This restricts the agent to only fetch data from specific endpoints like listtournaments. It keeps your indexing pipelines clean and focused.

Index live soccer data and match statistics directly into your LlamaIndex vector store.

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Connect Broadage Sports MCP to LlamaIndex

Create your Vinkius account to connect Broadage Sports to LlamaIndex 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 Broadage Sports with LlamaIndex

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Grounding your index with live sports data

The `get_match_summary` tool fetches current scores and match summaries to keep your knowledge index accurate. LlamaIndex ingestion pipelines can run this tool periodically to update your vector database with the latest pitch results. This prevents your agent from hallucinating historical scores or tournament standings. You get factual, timestamped match summaries stored right alongside your static documents.

Querying historical match events via this MCP Server

This Broadage Sports MCP Server lets you index granular event timelines using `get_match_events` and `get_match_stats` for semantic search. When users ask about late-game goals or possession trends, LlamaIndex searches the indexed tool outputs instead of hitting external APIs repeatedly. You build a queryable archive of team performances over time. The agent retrieves the exact stats needed from the index to answer complex analytical questions instantly.

Context-aware team and tournament indexing

You can use `list_team_players` and `list_tournaments` to build a structured database of active leagues and rosters. Your LlamaIndex application maps these relationships, making it easy to search for player histories or tournament structures. By combining these lookup tools, your system understands which players belong to which squads before a match even starts. It turns raw API outputs into a highly connected knowledge graph.

Setup guide

Set up Broadage Sports MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Broadage Sports MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Broadage Sports tools.",
)
response = await agent.run("List recent Broadage Sports data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Broadage Sports. 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 Broadage Sports MCP in LlamaIndex

You start by installing the llama-index-tools-mcp package. After that, wrap the Vinkius client in an McpToolSpec. Finally, convert it to a tool list and pass it to your FunctionAgent.

No, it queries the live server endpoint directly unless you configure a custom caching layer in your storage context. This ensures your semantic search queries always return the most up-to-date sports data. You can control cache expiration based on match schedules.

Yes, this is highly effective. You can run cron jobs to fetch match events with `get_match_events` and index them as document nodes. Users can then query your vector store for specific match highlights.

You use the allowed_tools filter when setting up your tool specification. This restricts the agent to only fetch data from specific endpoints like `list_tournaments`. It keeps your indexing pipelines clean and focused.

Your parsed match summaries and tournament logs are processed entirely in memory through the Vinkius MCP sandbox. Vinkius executes each tool call inside an isolated environment, ensuring your proprietary search index queries remain confidential.

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