GameScorekeeper MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect GameScorekeeper through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"gamescorekeeper": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using GameScorekeeper, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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.
LangChain's ecosystem of 500+ components combines seamlessly with GameScorekeeper through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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 LangChain 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 LangChain via MCP
Follow these steps to integrate the GameScorekeeper MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from GameScorekeeper via MCP
Why Use LangChain with the GameScorekeeper MCP Server
LangChain provides unique advantages when paired with GameScorekeeper through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine GameScorekeeper MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across GameScorekeeper queries for multi-turn workflows
GameScorekeeper + LangChain Use Cases
Practical scenarios where LangChain combined with the GameScorekeeper MCP Server delivers measurable value.
RAG with live data: combine GameScorekeeper tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query GameScorekeeper, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain GameScorekeeper tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every GameScorekeeper tool call, measure latency, and optimize your agent's performance
GameScorekeeper MCP Tools for LangChain (10)
These 10 tools become available when you connect GameScorekeeper to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain agent to start working with GameScorekeeper immediately.
"Show me the upcoming Champions League fixtures."
Troubleshooting GameScorekeeper MCP Server with LangChain
Common issues when connecting GameScorekeeper to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersGameScorekeeper + LangChain FAQ
Common questions about integrating GameScorekeeper MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect GameScorekeeper 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 GameScorekeeper to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.