# Stockfish

> Use this tool when you need to integrate world-class chess analysis into AI applications, providing programmatic access to chess engine capabilities for game evaluation, move suggestion, and educational tools. It accepts UCI protocol commands as input and outputs chess analysis results, supporting configurable search operations and evaluation parameters. Ideal for use cases requiring direct access to chess engine analysis, such as game development, educational platforms, and AI-powered chess assistants.

Canonical page: https://skillsregistry.net/skills/stockfish  
JSON: https://api.skillsregistry.net/v1/skills/stockfish

## Description

MCP server implementation by sonirico that provides AI assistants with direct access to the Stockfish chess engine through UCI (Universal Chess Interface) protocol commands. Built in Go with both persistent and ephemeral session management, the server supports standard UCI commands like position setup, move analysis, engine configuration, and search operations with configurable depth, time limits, and evaluation parameters. The implementation offers flexible deployment options including Docker containerization and HTTP/stdio transport modes, with comprehensive session lifecycle management, command validation, and timeout handling. Designed for AI applications requiring chess analysis capabilities, game evaluation workflows, move suggestion systems, and educational chess tools where programmatic access to world-class chess engine analysis is needed without managing complex UCI protocol interactions directly.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-19

## Source

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

## 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": "stockfish"
    }
  }
}
```

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