# tic-tac-toe

> tic-tac-toe — nirajbagdi-tic-tac-toe. Use this tool when you need to simulate a game of tic-tac-toe, either against another player or an AI opponent, with the ability to manage and track game state through an MCP server, accepting input in the form of player moves and outputting the updated game board. It solves problems related to game development, AI testing, and multiplayer functionality. Ideal for use cases involving competitive gaming, AI training, or social gaming platforms.

Canonical page: https://skillsregistry.net/skills/nirajbagdi-tic-tac-toe  
JSON: https://api.skillsregistry.net/v1/skills/nirajbagdi-tic-tac-toe

## Description

Tic-tac-toe with an MCP server

## Trust

- **Trust score (0–1):** 0.93
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/nirajbagdi/tic-tac-toe)

## 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": "nirajbagdi-tic-tac-toe"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nirajbagdi-tic-tac-toe` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nirajbagdi-tic-tac-toe/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