How to Use the API-Football MCP in Pydantic AI

Build type-safe football data agents with Pydantic AI and API-Football.

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Connect API-Football MCP to Pydantic AI

Create your Vinkius account to connect API-Football to Pydantic AI 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 API-Football with Pydantic AI

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Validate Match Data with Pydantic AI

The API-Football MCP Server ensures every match fixture matches your application's expected schema. By calling `get_fixtures` and `list_live_fixtures`, your agent parses live scores and match dates with strict runtime validation. If the external API returns unexpected or corrupted data, the framework raises a validation error immediately. This prevents bad data from breaking your database or downstream pipelines.

Query Standings via MCP Server

The API-Football MCP Server pulls current league tables using `get_standings` and `list_leagues`. Validation of the returned league structures happens automatically, making sure team IDs and points are formatted correctly before processing. Since this toolset is model-agnostic, you can use it with OpenAI, Anthropic, or local models. The validation layer remains identical regardless of the LLM you choose.

Type-Checked Player Analytics

The API-Football MCP Server runs clean queries for player stats using `get_player_info` and `get_league_topscorers`. Goals, appearances, and cards are extracted cleanly without risking silent errors from missing fields. To set this up, run your server externally and connect via the unified MCPToolset class. Pass the toolset directly to your Agent constructor to begin querying.

Setup guide

Set up API-Football MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "api-football-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to API-Football tools.",
)

result = await agent.run("List recent API-Football transactions")
print(result.output)

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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 API-Football. 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 API-Football MCP in Pydantic AI

Install the slim package with the mcp extra, then instantiate MCPToolset pointing to your HTTP endpoint. Pass this toolset into the toolsets list when creating your Agent.

The framework will catch the discrepancy at runtime and raise a validation error. This keeps your system from processing malformed football stats or corrupted standings.

Yes. The framework is model-agnostic, meaning you can query football fixtures and player data using local models or commercial APIs.

No. The server runs externally on our managed infrastructure. You connect to it using the streamable HTTP or SSE transport options.

All requests for team details, match fixtures, and player stats are processed in isolated, ephemeral environments. We do not log the contents of your queries or store any football data retrieved during execution.

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