Football-Data.org MCP Server for Pydantic AIGive Pydantic AI instant access to 14 tools to Get Area, Get Competition, Get Competition Standings, and more

Name: Football-Data.org
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Football-Data.org through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The Football-Data.org MCP Server for Pydantic AI is a standout in the Data Analytics category — giving your AI agent 14 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Football-Data.org "
            "(14 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Football-Data.org?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

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* 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 Football-Data.org MCP Server

Connect the Football-Data.org API to your AI agent to retrieve comprehensive football (soccer) data through natural language. Stay updated with live scores, historical results, and deep team analytics.

Pydantic AI validates every Football-Data.org tool response against typed schemas, catching data inconsistencies at build time. Connect 14 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

League Standings — Fetch real-time tables for the Premier League, La Liga, Bundesliga, Serie A, and more using get_competition_standings.
Match Tracking — Query upcoming fixtures or past results for specific competitions or teams with list_competition_matches and list_team_matches.
Top Scorers — Identify the leading goal scorers in any supported tournament using list_competition_scorers.
Team & Player Insights — Get detailed profiles, squad lists, and individual player performance history via get_team and get_player.
Global Coverage — Explore football data across different geographical areas and continents using list_areas.

The Football-Data.org MCP Server exposes 14 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 14 Football-Data.org tools available for Pydantic AI

When Pydantic AI connects to Football-Data.org through Vinkius, your AI agent gets direct access to every tool listed below — spanning real-time-scores, sports-analytics, api-integration, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get area on Football-Data.org

Get details for a specific area

get

Get competition on Football-Data.org

g., PL for Premier League). Get details for a specific competition

get

Get competition standings on Football-Data.org

Can be filtered by standing type (TOTAL, HOME, AWAY). Get standings (league table) for a competition

get

Get match on Football-Data.org

Get details for a specific match

get

Get player on Football-Data.org

Get details for a specific player

get

Get team on Football-Data.org

Get details for a specific team

list

List areas on Football-Data.org

List all geographical areas

list

List competition matches on Football-Data.org

Can be filtered by season, status, stage, group, date range, or matchday. List matches for a specific competition

list

List competition scorers on Football-Data.org

List top scorers for a competition

list

List competition teams on Football-Data.org

List teams in a specific competition

list

List competitions on Football-Data.org

Can be filtered by specific competition IDs or season. List available competitions

list

List matches on Football-Data.org

List matches across competitions

list

List player matches on Football-Data.org

List matches for a specific player

list

List team matches on Football-Data.org

Can be filtered by status, venue, and date range. List matches for a specific team

Connect Football-Data.org to Pydantic AI via MCP

Follow these steps to wire Football-Data.org into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install Pydantic AI

Run pip install pydantic-ai

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 14 tools from Football-Data.org with type-safe schemas

Why Use Pydantic AI with the Football-Data.org MCP Server

Pydantic AI provides unique advantages when paired with Football-Data.org through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Football-Data.org integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Football-Data.org connection logic from agent behavior for testable, maintainable code

Football-Data.org + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Football-Data.org MCP Server delivers measurable value.

Type-safe data pipelines: query Football-Data.org with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Football-Data.org tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Football-Data.org and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Football-Data.org responses and write comprehensive agent tests

Example Prompts for Football-Data.org in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Football-Data.org immediately.

"Show me the current Premier League standings."

"Who are the top scorers in the Champions League right now?"

"What are the next 3 matches for Real Madrid?"

Troubleshooting Football-Data.org MCP Server with Pydantic AI

Common issues when connecting Football-Data.org to Pydantic AI through Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Football-Data.org + Pydantic AI FAQ

Common questions about integrating Football-Data.org MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Football-Data.org MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.

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