Chess UCI
Connect to UCI-compatible chess engines like Stockfish to play and analyze games. Requires a local chess engine binary.
chess-uci-mcp
An MCP bridge that provides an interface to UCI chess engines (such as Stockfish).
Dependencies
You need to have Python 3.10 or newer, and also uv/uvx installed.
Usage
To function, it requires an installed UCI-compatible chess engine, like Stockfish (has been tested with Stockfish 17).
In case of Stockfish, you can download it from https://stockfishchess.org/download/.
On macOS, you can use brew install stockfish.
You need to find out the path to your UCI-capable engine binary; for further example configuration, the path is e.g. /usr/local/bin/stockfish (which is default for Stockfish installed on macOS using Brew).
The further configuration should be done in your MCP setup;
for Claude Desktop, this is the file claude_desktop_config.json (find it in Settings menu, Developer, then Edit Config).
The full path on different OSes
- macOS:
~/Library/Application\ Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%/Claude/claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
Add the following settings to your MCP configuration (depending on the way to run it you prefer):
Uvx (recommended)
Uvx is able to directly run the Python application by its name, ensuring all the dependencies, in a automatically-created virtual environment.
This is the preferred way to run the chess-uci-mcp bridge.
Set up your MCP server configuration (e.g. Claude Desktop configuration) file as following:
"mcpServers": {
"chess-uci-mcp": {
"command": "uvx",
"args": ["chess-uci-mcp@latest", "/usr/local/bin/stockfish"]
}
}
To pass options to the engine, add them to the args array. For example, to set the Threads and Hash options for Stockfish:
"mcpServers": {
"chess-uci-mcp": {
"command": "uvx",
"args": [
"chess-uci-mcp@latest",
"/usr/local/bin/stockfish",
"-o", "Threads", "4",
"-o", "Hash", "128"
]
}
}
Uv
Use it if you have the repository cloned locally and run from it:
"mcpServers": {
"chess-uci-mcp": {
"command": "uv",
"args": ["run", "chess-uci-mcp", "/usr/local/bin/stockfish"]
}
}
Similarly, to pass options when running with uv:
"mcpServers": {
"chess-uci-mcp": {
"command": "uv",
"args": [
"run",
"chess-uci-mcp",
"/usr/local/bin/stockfish",
"-o", "Threads", "4",
"-o", "Hash", "128"
]
}
}
Command-line Options
The application accepts the following command-line options:
ENGINE_PATH: (Required) The path to the UCI-compatible chess engine executable.--uci-optionor-o: Set a UCI option. This option can be used multiple times. It takes two arguments: the option name and its value (e.g.,-o Threads 4).--think-time: The default thinking time for the engine in milliseconds. Defaults to1000.--debug: Enable debug logging.
Available MCP Commands
The bridge provides the following MCP commands:
analyze- Analyze a chess position specified by FEN stringget_best_move- Get the best move for a chess positionset_position- Set the current chess positionengine_info- Get information about the chess engine
Development
# Clone the repository
git clone https://github.com/AnglerfishChess/chess-uci-mcp.git
# ... or
# git clone [email protected]:AnglerfishChess/chess-uci-mcp.git
cd chess-uci-mcp
# Create a virtual environment
uv venv --python python3.10
# Activate the virtual environment
source .venv/bin/activate # On Unix/macOS
# or
.venv\Scripts\activate # On Windows
# Install the package in development mode
# uv pip install -e .
# or, with development dependencies
uv pip install -e ".[dev]"
# Resync the packages:
uv sync --extra=dev
# Run tests
pytest
# Check code style
ruff check
Release process
- Bump version in
pyproject.toml,chess_uci_mcp/__init__.pyanduv.lock. - Build and publish:
uv build
uv-publish
We use uv-publish (install via uvx uv-publish or as dev dependency) because it automatically reads PyPI credentials from ~/.pypirc.
- Tag and push:
git tag v0.x.x
git push && git push --tags
Related sites
Related Servers
UUč·č æ MCP Server
Create orders on the uupt.com open platform using the MCP protocol.
Weather Service MCP Server
A Spring Boot-based weather service providing weather forecasts and alerts via MCP integration.
stock-scanner
49-tool MCP server for stock and crypto market data ā quotes, technicals, SEC filings, insider trades, options flow, earnings, and sentiment analysis. 7 modules work with zero API keys
Sidekick for InDesign
Lets your AI assistant talk to InDesign. Not about it. Actually control it.
Fabric MCP Server
The Fabric MCP server exposes the following MCP tools that allow AI assistants to interact with your Equinix Fabric resources. Each tool corresponds to a specific Fabric API endpoint.
Nexbid
Agentic commerce infrastructure for AI agents. MCP-native product discovery, contextual ad matching, and purchase facilitation with European privacy compliance (nDSG/GDPR).
LinkedIn Ads MCP
Connect LinkedIn Ads to Claude or ChatGPT via Two Minute Reports MCP to get clear insights into campaign performance, impressions, CTR, CPC, leads, and conversions.
AI Bill of Materials (AI-BOM) MCP
Generate AI Bills of Materials for model supply chain transparency ā tracks datasets, training provenance, model cards, and dependency graphs per emerging AI-BOM standards.
PancakeSwap PoolSpy
Tracks newly created liquidity pools on PancakeSwap, providing real-time data for DeFi analysts, traders, and developers.
GuessMarket MCP
Prediction market trading server for GuessMarket. Browse markets, buy/sell shares, add/remove liquidity, check portfolios, and build on-chain transactions. 20+ tools.