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
相關伺服器
Hidden Empire
Play a legendary text adventure by talking to your AI — no commands to memorize. The Hidden Empire puts a full underground world of puzzles, treasures, and trolls inside your conversation. Speak naturally: say 'head north,' 'grab the lantern,' or 'what am I carrying?' and your AI handles the rest. Execute multi-move plans in one shot, undo mistakes instantly, and save up to 20 named playthroughs you can resume from any session. Based on the MIT-licensed Zork I source, rebuilt from the ground up for AI-native play.
Agent Central
Hosted MCP server for Amazon sellers using Claude, ChatGPT, and other AI clients.
Search Movie
一个基于 Model Context Protocol (MCP) 构建的智能电影和电视剧资源搜索工具,支持多源搜索和链接验证。An intelligent movie and TV series resource search tool based on Model Context Protocol (MCP), supporting multi-source search and link verification.
Fathom
Financial intelligence for AI agents — 31 tools across 8 data sources including regime, derivatives, stablecoin flows, momentum, macro, weather patterns, and political cycles.
MCP.science
A collection of open-source MCP servers designed for scientific research applications.
Peec AI
Monitor and analyze your brand's visibility across AI search engines. Track your visibility, sentiment, and share of voice & compare to competitors.
Medical Writer's AI Toolkit
30+ pharma medical writing prompts as callable MCP tools — manuscripts, abstracts, publication plans and more. Built by a CMPP-certified PhD neuroscientist.
ALTER
ALTER - identity infrastructure for the AI economy
Smart Home Device Control
Control smart home devices and query information by connecting large models to smart home backend APIs.
Arkheia Hallucination Detection
Detect fabrication and hallucination in any LLM output. Score responses from GPT-4o, Claude, Gemini, Llama and 30+ models. Free tier included.