GameScorekeeper MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add GameScorekeeper 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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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 GameScorekeeper. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in GameScorekeeper?"
)
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 GameScorekeeper MCP Server
Connect GameScorekeeper to your AI agent for real-time football (soccer) intelligence across major competitions.
LlamaIndex agents combine GameScorekeeper tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Competitions — Browse and list active competitions with detailed metadata
- Fixtures — Get fixture schedules, live scores, and match results
- Lineups — Access full match lineups with player positions and numbers
- Team Intelligence — View team profiles, current form, and recent results
- Player Stats — Access individual player statistics, career data, and performance metrics
- Stage Navigation — Browse competition stages (group stage, knockouts, etc.)
The GameScorekeeper MCP Server exposes 10 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 GameScorekeeper to LlamaIndex via MCP
Follow these steps to integrate the GameScorekeeper 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 10 tools from GameScorekeeper
Why Use LlamaIndex with the GameScorekeeper MCP Server
LlamaIndex provides unique advantages when paired with GameScorekeeper through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine GameScorekeeper tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain GameScorekeeper tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query GameScorekeeper, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what GameScorekeeper tools were called, what data was returned, and how it influenced the final answer
GameScorekeeper + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the GameScorekeeper MCP Server delivers measurable value.
Hybrid search: combine GameScorekeeper real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query GameScorekeeper 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 GameScorekeeper for fresh data
Analytical workflows: chain GameScorekeeper queries with LlamaIndex's data connectors to build multi-source analytical reports
GameScorekeeper MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect GameScorekeeper to LlamaIndex via MCP:
get_competition_details
Get detailed info for a specific tournament
get_fixture_details
Get detailed match information
get_fixture_lineup
Get player lineups for a specific match
get_player_details
Get individual player profile
get_player_stats
Retrieve historical performance metrics for a player
get_team_details
Get basic information and logo for an esports team
get_team_form
Get recent performance form for a team
list_competition_stages
List stages (e.g., Playoffs, Group Stage) for a competition
list_competitions
List all supported esports tournaments and leagues
list_fixtures
List upcoming and past esports matches
Example Prompts for GameScorekeeper in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with GameScorekeeper immediately.
"Show me the upcoming Champions League fixtures."
Troubleshooting GameScorekeeper MCP Server with LlamaIndex
Common issues when connecting GameScorekeeper to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGameScorekeeper + LlamaIndex FAQ
Common questions about integrating GameScorekeeper 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 GameScorekeeper with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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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 GameScorekeeper to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.