# Footalytics [Health: Active]

**Category:** 🏃 Sports  
**Repository:** https://footalytics.farvor.com/mcp  
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**Directory Page:** https://allmcps.com/mcp/footalytics

## Description
Remote Streamable HTTP MCP with OAuth for graded football predictions, fixtures, team ratings and settled results. Free starter allowance.

## Tools
Capabilities this server exposes over MCP:

- **get_match_prediction** — AI football prediction: combines the algorithm with live data, analyses the match in depth, and predicts the score. Returns win/draw/loss probabilities, confidence, Over/Under 2.5 and Both-Teams-To-Score. Keep those numbers in the answer. Team names must be English (Arsenal, not 阿森纳). Uses 1 credit per successful call. Identify the match with fixture=<id> OR home+away (date optional, UTC).
- **get_account_credits** — Remaining Footalytics credits on the connected account. Call this before a prediction when the user asks about their quota, or when a prediction call failed with insufficient_credits.
- **list_fixtures** — Upcoming football fixtures with fixture ids and a has_prediction flag (1 credit per successful call). Use it to discover matches, then call get_match_prediction with the fixture id or English team names.
- **get_team** — Team profile from the Footalytics ratings table: current rating, games tracked and league (1 credit per successful call).
- **list_results** — Settled official predictions with the real score and the grade — hit/miss per market and Brier score; the public accuracy record (1 credit per successful call).

## Claude Desktop Quick Installation
Remote MCP endpoint (confidence: medium). Install path inferred — verify against the README before running it. Add as a URL/SSE server in your client:

```json
"mcpServers": {
  "footalytics": {
    "url": "https://footalytics.farvor.com/mcp"
  }
}
```

## Documentation

## What Footalytics does

Footalytics provides football-focused data and analysis through the Model Context Protocol. Its capabilities cover four main areas: graded football predictions, fixtures, team ratings, and settled results. These categories support agents that need to inspect upcoming or historical football information, compare team strength, or review how predictions performed after matches were settled.

The service is aimed at AI clients rather than direct human use. Once connected, an MCP-compatible assistant can request the available football information as part of a conversation or an agent workflow. The Sports category is relevant for developers building football research, prediction-review, or fixture-analysis assistants.

## How it works

Footalytics is exposed as a remote Streamable HTTP MCP endpoint at `https://footalytics.farvor.com/mcp`. Instead of launching a local server process, an MCP client connects to that URL and communicates with the service over HTTP using the Streamable HTTP transport.

Access uses OAuth. A client must therefore complete the service's authorization flow before it can use the protected MCP capabilities. After authorization, the connected agent can work with the football data exposed by Footalytics, including predictions, fixtures, ratings, and settled outcomes.

This remote arrangement can be useful when the client environment should consume a hosted football service rather than manage a local installation. It also means the agent's access depends on the remote endpoint and its authentication flow being available.

## Limitations and notes

Footalytics includes a free starter allowance, which gives developers a way to begin using the service before selecting a broader access arrangement. The service is remote, so network access is required; it is not described as a package that runs independently on the client machine.

OAuth is part of the connection model and should be treated as a setup requirement. The available subject matter is specifically football, with the documented scope centered on graded predictions, fixtures, team ratings, and settled results. Developers looking for unrelated sports data or general-purpose analytics should evaluate whether those football-specific capabilities fit their workflow.

_Full upstream README: https://allmcps.com/mcp/footalytics/readme_