How to Use the API-Football MCP in CrewAI

Q: How do I expose API-Football tools to a specific CrewAI agent?

You can pass the MCP Server URL directly in the agent's mcps list. For more control, use MCPServerHTTP to filter exactly which tools each agent can use.

Deploy a collaborative crew of AI agents to analyze football matches and player statistics with CrewAI.

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Connect API-Football MCP to CrewAI

Create your Vinkius account to connect API-Football to CrewAI 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 CrewAI

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Perplexity

Coordinate agents using the API-Football MCP Server

Providing schedules to your researcher agent starts with `get_fixtures`. While that agent gathers upcoming match lists, a separate analyst agent uses the data to prepare tactical reports. Sharing context and memory allows them to produce deeper match previews than a single agent could.

Build an autonomous player scouting crew

Scouting agents get instant access to player stats and performance history using `get_player_info`. The scout agent evaluates the raw metrics and passes the profile to a manager agent. If the profile looks promising, the manager agent uses `search_football_teams` to find potential transfer destinations. The entire process runs autonomously from start to finish.

Track league standings with specialized crews

Keeping tabs on league tables is simple when your monitoring agent runs `get_standings`. As soon as a position shifts, the agent alerts the content writer agent to draft a summary. Using the MCP standard, you can limit which tools each agent can access. This keeps your agents focused on their specific roles without wasting tokens on irrelevant API calls.

Setup guide

Set up API-Football MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke API-Football tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="API-Football Analyst",
    goal="Access and analyze API-Football data via MCP.",
    backstory="Expert analyst with direct API-Football access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent API-Football transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="API-Football Analyst",
        goal="Access and analyze API-Football data via MCP.",
        backstory="Expert analyst with direct API-Football access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent API-Football transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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 CrewAI

You can pass the MCP Server URL directly in the agent's `mcps` list. For more control, use `MCPServerHTTP` to filter exactly which tools each agent can use.

Yes, CrewAI agents share a common memory space. Once one agent pulls standings using `get_standings`, that data is available to the rest of the crew.

The simplest method is passing the MCP HTTP endpoint to the agent's configuration. The framework handles the underlying tool registration automatically.

This setup supports stdio, SSE, and Streamable HTTP transports. You can choose the one that fits your deployment architecture best.

Yes, all match inquiries and team IDs are processed within a secure MCP sandbox. No data is stored permanently on Vinkius servers.

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