We are designing a set of MCP tools for working with the Stockfish engine and an open chess game database. The goal is simple: turn game review into a clear workflow for training, finding weak spots, and preparing openings.
The service will be able to find key mistakes, recurring position types, and moments where the plan matters more than a single exact move. This kind of review helps explain not only the blunder, but also the decision behind it.
The game database can help prepare for a specific player: favorite structures, common openings, typical endgames, and positions where the opponent often deviates from the strongest lines.
The tools will help build a repertoire from real games, verify lines with the engine, and connect variations to practical ideas: where to place pieces, which plans to choose, and what to avoid.
The MCP layer can become a bridge between the chess engine, game collections, and a personal spaced-repetition system. Not just “+0.7”, but useful context: who played this way, which plans appeared, and how to use the idea in your next game.