# Footics MCP

> Use this tool when you need to interact with the Footics World Cup 2026 prediction game, enabling AI assistants to read matches, standings, and predictions, and optionally submit predictions to participate in the game. It solves problems related to accessing and engaging with the game's data and functionality. The tool accepts input such as match IDs and prediction data, and outputs relevant game information, making it ideal for use cases involving sports prediction and gaming applications.

Canonical page: https://skillsregistry.net/skills/footics-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/footics-mcp-server

## Description

Enables AI assistants to interact with the Footics World Cup 2026 prediction game, reading matches, standings, predictions, and optionally submitting predictions.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/flesjixcw0)
- **Repository:** <https://github.com/Footics/mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "footics-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/footics-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/footics-mcp-server/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt