# Chess

> Use this tool when you need to engage in strategic gameplay or analyze chess positions with AI assistants. It solves problems of limited interactive gameplay and chess analysis capabilities in conversational interfaces, providing a visual board and move-making tools. The tool takes PGN notation as input and outputs a visualized chess board, making it ideal for users who want to play chess or discuss chess strategies with LLMs.

Canonical page: https://skillsregistry.net/skills/jiayao-chess  
JSON: https://api.skillsregistry.net/v1/skills/jiayao-chess

## Description

MCP Chess Server enables playing chess against any LLM through a visual interface. It provides tools for visualizing the board, making moves, starting new games with customizable player colors, and analyzing positions from PGN notation. The server uses the Python chess library for game logic and CairoSVG for rendering board visualizations, making it ideal for users who want to engage in chess matches with AI assistants or analyze specific chess positions during conversations.

## Trust

- **Trust score (0–1):** 0.92
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/jiayao-chess)
- **Repository:** <https://github.com/jiayao/mcp-chess>

## 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": "jiayao-chess"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jiayao-chess` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jiayao-chess/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