Shogi MCP Server
Related Servers
Alternatives to Shogi MCP Server
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to play and analyze chess, validate moves, and view a live synchronized visual board in the browser through MCP tools.13 npmMIT
- AlicenseNot gradedqualityAmaintenanceAn MCP bridge that provides an interface to UCI-compatible chess engines like Stockfish for analyzing positions and retrieving best moves. It enables users to interact with chess engines through commands for position management, engine information, and move calculation.2MIT
- FlicenseAqualityDmaintenanceEnables chess analysis and move generation using the Stockfish engine via MCP tools, allowing clients to evaluate positions, get best moves, apply moves, and visualize boards.7-
- AlicenseNot gradedqualityCmaintenanceEnables chess position analysis, legal move investigation, move comparison, and PGN game reconstruction through MCP tools.MIT
- AlicenseAqualityBmaintenanceMCP chess runtime that lets LLMs play, analyze, and adapt strength by exposing Stockfish, human move likelihood (Maia3), and Lichess statistics, with the LLM handling strategy and the server handling computation.13274 npmAGPL 3.0
- AlicenseNot gradedqualityDmaintenanceA powerful chess engine and game server built with the Model Context Protocol (MCP). Play chess against AI, analyze positions, and integrate chess functionality into your AI applications.13 npm1ISC
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: 'analyze' evaluates the current position, 'eval_at' analyzes a specific move from the current position, and 'ping' is a health check. There is no overlap in functionality, making tool selection unambiguous for an agent.
The naming is mostly consistent with a verb-based pattern ('analyze', 'eval_at', 'ping'), though 'eval_at' uses an underscore while the others do not, and 'ping' is a simple verb rather than a descriptive action. This minor deviation keeps the set readable but not perfectly uniform.
With only 3 tools, the set feels thin for a Shogi server, as it lacks operations like move generation, game state management, or board manipulation. While the tools cover core analysis, the count is borderline for the domain's potential scope.
The tool surface has significant gaps for a Shogi server: there are no tools for creating or modifying game states (e.g., making moves, resetting boards), accessing game history, or handling game rules. This incompleteness will likely cause agent failures in broader Shogi-related tasks.