How to integrate Api sports MCP with Mastra AI

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Introduction

This guide walks you through connecting Api sports to Mastra AI using the Composio tool router. By the end, you'll have a working Api sports agent that can show today's football fixtures for la liga, get head-to-head record for chelsea vs arsenal, list injured players in premier league this week, fetch starting lineup for tonight's psg match through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Api sports account through Composio's Api sports MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Api sports tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Api sports tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Api sports agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

What is the Api sports MCP server, and what's possible with it?

The Api sports MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Api sports account. It provides structured and secure access to rich sports data, so your agent can fetch fixtures, analyze team stats, retrieve player info, and explore historical match data on your behalf.

  • Live fixture and match retrieval: Instantly access upcoming and past football fixtures, filterable by league, team, date, or season for up-to-date match information.
  • Detailed match statistics and events: Have your agent pull granular match data, including goals, cards, substitutions, and in-depth statistics like possession, fouls, and passes for any fixture.
  • Team, coach, and player insights: Effortlessly fetch team rosters, coach histories, and individual player statistics or injury reports, making it easy to analyze team lineups and track player performance over time.
  • Head-to-head comparisons and historical data: Ask your agent to compare two teams’ direct matchups, review historical data, or examine league rounds, helping you make informed predictions or reports.
  • Dynamic country and league exploration: Let your agent discover available countries, leagues, and competitions, then drill down by code or search to tailor your sports data queries to specific needs.

Supported Tools & Triggers

Tools
Get CoachesTool to fetch coaches and their career history.
Get CountriesTool to fetch available countries for league queries.
Get FixturesTool to retrieve football fixtures/matches.
Get fixtures eventsTool to get events (goals, cards, substitutions, var, etc.
Get Head-to-Head FixturesTool to get head-to-head fixtures between two teams.
Get Fixture LineupsTool to retrieve starting xi and substitutes for a fixture.
Get fixtures playersTool to get player statistics from a fixture.
Get Fixtures RoundsTool to get the rounds for a league or cup.
Get fixture statisticsTool to get statistics for a fixture.
Get InjuriesTool to get injured or suspended players.
Get LeaguesTool to retrieve leagues and cups.
Get League SeasonsTool to get the list of available seasons for all leagues.
Get OddsTool to fetch pre-match odds.
Get Odds BetsTool to get all available pre-match bet types.
Get Odds BookmakersTool to list all available pre-match bookmakers.
Get In-Play OddsTool to fetch in-play odds for fixtures in progress.
Get Live Odds BetsTool to fetch all available bet types for in-play odds.
Get PlayersTool to get player statistics.
Get Players ProfilesTool to get the list of all available players.
Get Players SeasonsTool to list all available seasons for player statistics.
Get Players TeamsTool to get the list of teams and seasons in which a player played during his career.
Get Players Top AssistsTool to get the 20 best players (top assists) for a league or cup.
Get Players Top ScorersTool to get the 20 best players (top scorers) for a league or cup.
Get Players Top Yellow CardsTool to get the 20 players with the most yellow cards for a league or cup.
Get PredictionsTool to get predictions about a fixture.
Get SidelinedTool to get sidelined information (injuries, suspensions, etc.
Get TeamsTool to retrieve available teams.
Get team statisticsTool to get detailed statistics of a team for a given league and season.
Get TimezoneTool to fetch the complete list of available timezones for fixture queries.
Get TransfersTool to get all available transfers for players and teams.
Get TrophiesTool to get trophies for a player or coach.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Api sports through MCP.

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session

Create a Tool Router session for Api sports

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["api_sports"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Api sports MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "api_sports" for Api sports access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Api sports toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "api_sports-mastra-agent",
    instructions: "You are an AI agent with Api sports tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        api_sports: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Api sports toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Api sports and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["api_sports"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      api_sports: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "api_sports-mastra-agent",
    instructions: "You are an AI agent with Api sports tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { api_sports: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Api sports through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows

How to build Api sports MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Api sports MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Api sports MCP with Claude Agent SDK

Google ADK

Google ADK

Use Api sports MCP with Google ADK

LangChain

LangChain

Use Api sports MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Api sports MCP with Vercel AI SDK

LlamaIndex

LlamaIndex

Use Api sports MCP with LlamaIndex

CrewAI

CrewAI

Use Api sports MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Api sports MCP?

With a standalone Api sports MCP server, the agents and LLMs can only access a fixed set of Api sports tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Api sports and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with Mastra AI?

Yes, you can. Mastra AI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Api sports tools.

Can I manage the permissions and scopes for Api sports while using Tool Router?

Yes, absolutely. You can configure which Api sports scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Api sports data and credentials are handled as safely as possible.

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