How to Use the Broadage Sports MCP in Mastra AI

Q: How do I handle API failures when using Broadage Sports with Mastra AI?

Mastra AI has built-in exponential backoff. If getmatchstats fails due to network issues, the framework automatically retries the tool call before failing the workflow.

Q: Can I build conditional sports alerts with Broadage Sports and Mastra AI?

Yes. You can set up a Mastra workflow that runs listlivematches, checks if a specific team is playing, and branches to getmatchevents only when a goal occurs.

Build automated sports workflows with Mastra AI, running conditional logic on live soccer scores and match statistics.

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Connect Broadage Sports MCP to Mastra AI

Create your Vinkius account to connect Broadage Sports to Mastra 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 Broadage Sports with Mastra AI

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Automated match tracking with Mastra AI

`list_live_matches` operates within Mastra workflows to monitor soccer games automatically. You can build a system that checks active matches every five minutes and triggers notifications when goals are scored. If a match goes to extra time, Mastra handles the conditional branching to keep tracking. This MCP Server integrates directly with Mastra's built-in step execution. The framework retries failed requests with exponential backoff if the network drops, ensuring you never miss a kickoff.

Roster alerts and player checks

`get_match_lineup` lets your agent verify starting lineups before a game starts. Mastra workflows can wait for this data, check for specific key players using `list_team_players`, and alert your users if a star striker is benched. You write the logic once, and Mastra executes it reliably. Using this MCP Server, your agents can compare lineups across different dates. Your workflows branch based on whether a team plays their primary squad or reserves.

Game analysis loops

`get_match_stats` feeds detailed game statistics into Mastra's context window for deep post-match analysis. Your agent can run a loop comparing possession and shots to the final score from `get_match_summary`. If stats show an outlier, Mastra can spin up a sub-agent to investigate. This setup runs entirely on Mastra's serverless-friendly framework. You deploy the entire agentic loop to the cloud with a single command, keeping your sports analytics running 24/7.

Setup guide

Set up Broadage Sports MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Broadage Sports tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "broadage-sports-mcp-client",
  servers: {
    "broadage-sports-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Broadage Sports Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Broadage Sports tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Broadage Sports transactions"
);
console.log(result.text);

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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 Broadage Sports. 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 Broadage Sports MCP in Mastra AI

Mastra AI has built-in exponential backoff. If get_match_stats fails due to network issues, the framework automatically retries the tool call before failing the workflow.

Yes. You can set up a Mastra workflow that runs list_live_matches, checks if a specific team is playing, and branches to get_match_events only when a goal occurs.

You instantiate the MCP client, call listTools(), and spread those tools directly into your Mastra agent configuration. The framework handles the transport layer automatically.

Yes. Mastra supports human-in-the-loop validation, letting you approve or deny tool execution before the agent calls database-heavy tools.

All queries for team players and match events are executed in an ephemeral, zero-trust MCP sandbox. Your sports data searches are never stored or used to train public models.

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