A high-performance inference API endpoint for chess neural network policy evaluation, designed to integrate seamlessly with ChessAgine's MCP (Model Context Protocol) net tool. Overview This repository provides a REST API for running inference on chess position evaluation using ONNX-optimized neural networks. The API accepts chess positions in FEN notation and returns policy predictions for move evaluation, enabling real-time chess analysis and AI-powered decision making. Features
- Fast Inference: Leverages ONNX Runtime for optimized neural network inference
- Chess Position Analysis: Accepts positions in FEN format for universal compatibility
- Policy Network Evaluation: Returns move probabilities and policy predictions
- MCP Integration: Built specifically to work with ChessAgine's Model Context Protocol tools
- RESTful API: Simple HTTP endpoints for easy integration
GPL
- Hollowleaf for leela pre-proccessing code
- Maia devs for Maia class
- Lichess API
@jalpp