How to Use the API-Football MCP in LlamaIndex

Q: Does the API-Football integration with LlamaIndex support filtering?

Yes, you can use an allowedtools filter to restrict which data points enter your knowledge base. This keeps your index clean and focused.

Index live match statistics into your LlamaIndex knowledge base using the API-Football MCP Server.

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Connect API-Football MCP to LlamaIndex

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

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Build a searchable index for API-Football in LlamaIndex

Turn your API results into a queryable knowledge base. LlamaIndex takes output from `get_standings` and indexes it for semantic retrieval. Stop relying on static documents for sports data. Your agents now answer questions based on the latest league tables.

Ground AI answers in API-Football data

Use `get_team_info` to fetch details that your model then stores in a vector index. This stops the model from hallucinating stats. You gain a verifiable record of team history. Every answer your system provides references the actual API output.

Automate data ingestion from match fixtures

Run `get_fixtures` to pull schedules and index them for future queries. LlamaIndex parses these results into meaningful chunks for your agent. This approach turns a raw feed into a structured knowledge graph. You have total control over how the agent interprets the match data.

Setup guide

Set up API-Football MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all API-Football MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to API-Football tools.",
)
response = await agent.run("List recent API-Football data")

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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 LlamaIndex

Use the McpToolSpec to convert server tools into a format LlamaIndex understands. Once initialized, the agent will index the tool outputs automatically.

Yes, you can use an allowed_tools filter to restrict which data points enter your knowledge base. This keeps your index clean and focused.

By indexing live stats, your agent queries real match results rather than outdated training data. This grounds every response in current league facts.

Data privacy is handled at the transport layer by Vinkius. Your team information is never stored outside your isolated environment during the indexing process.

Yes, if you configure the index to retain past tool outputs. You can then perform semantic searches across previous match data.

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