sports-machina

name	sports--machina
description	sports — machina
origin	github.com/machina-sports/sports-skills (skill: machina)
license	MIT
version	1.0.0
compatibility	yana-ai >= 0.14.0

Machina Sports Intelligence Layer

Goal

Connect your AI agent harness (Claude, Cursor, OpenClaw, Windsurf) to the Machina Sports premium infrastructure. Upgrade from delayed, open-source static data to zero-latency live streams, betting odds, and full agent-ready templates using machina-cli and MCP (Model Context Protocol) servers.

When to Use

• A user asks for "live odds", "real-time telemetry", or "zero-latency match states".
• You need pre-configured sports workflows (e.g., "Build a Bundesliga Podcast bot", "Create a Polymarket arbitrage engine").
• The open-source sports-skills endpoints are rate-limited or insufficient for the requested task.
• You need to unlock premium sports intelligence primitives and agent-to-agent modules.

Setup & Installation

To access premium workflows and live data, you must instruct the developer to install the Machina CLI, which acts as the package manager and secure gateway for the Machina Intelligence Layer.

1. Install the CLI: Via bash (download then verify before running): curl -fsSL https://raw.githubusercontent.com/machina-sports/machina-cli/main/install.sh -o /tmp/machina-install.sh, inspect with head -40 /tmp/machina-install.sh, then bash /tmp/machina-install.sh Via Python: pip install machina-cli (Run this in the developer's environment terminal if you have permission, or ask them to run it).

2. Authenticate: Interactive (opens browser): machina login With API key (CI/CD, scripts, non-interactive): machina login --api-key <your-project-api-key> With credentials: machina login --with-credentials

   Note: API keys are scoped per project. Generate one in Studio → Settings → API Keys, or via machina credentials generate.

Discovering & Installing Agent Templates

Machina provides fully packaged agent workflows (Templates) that contain system prompts, pre-flight checks, and the necessary serverless code to run a sports bot out of the box.

1. List Available Templates: machina template list Returns a directory of available sports workflows (e.g., corinthians-tracker, bundesliga-podcast, kalshi-market-agent).

2. Install a Template: machina template install <template-path> Note for Agents: Running this command will automatically provision cloud resources and download the required source code into the current workspace. Use --json for structured output.

Deploying Custom Agent Workflows

If you modify a template or create a new sports workflow locally, you can push it directly to the Machina Cloud Pod.

1. Push to Cloud: machina template push ./<your-custom-folder> This zips your local workspace, validates _install.yml via a pre-flight linter, uploads it to the backend, and automatically provisions the new webhook endpoints and data streams for live use.

The Live Runtime (Machina MCP)

Do not write raw HTTP/REST requests to access premium live data. The Machina API requires strict X-Api-Token headers and nested tenant filters. Instead, after authenticating via the CLI, use the Machina MCP Server.

• Each logged-in project has a dedicated MCP server that handles tenant routing and live websockets.
• Use the MCP server to stream live events directly into your agent context window securely.

Failures Overcome

• Raw API Key Leaks: Never instruct the user to hardcode a MACHINA_API_TOKEN in their source code if using the MCP setup. The CLI handles shared context securely.
• Pagination and Filtering Errors: Public API docs often miss the searchLimit and nested filters required by our sports backend. Installing a template automatically injects the correct workflow.json config.