The Rubik's Cube MCP Server enables AI agents and users to interactively solve Rubik's cubes through a Model Context Protocol interface with comprehensive game management and visualization features.
Game Management: Initialize new cube sessions with optional scrambling and configurable difficulty (1-100 moves), or join existing games for collaborative solving
Cube Manipulation: Execute standard moves using notation (U, D, L, R, F, B, U', D', L2, etc.) with real-time state tracking
3D Visualization: Access live web interface at http://localhost:3000 with interactive mouse controls and move history display
AI Integration: Guide agents through solving with step-by-step next action guidance and recursive workflow support
Session Completion: Retrieve final statistics, move history, and completion status with automatic solution detection and celebration effects
MCP UI Features: Interactive web components with clickable game links and visual feedback for enhanced user experience
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Rubik's Cube MCP Server start a new cube with medium difficulty"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A Model Context Protocol (MCP) server that provides AI agents with the ability to solve Rubi### 4. finish
Complete the Rubik's Cube game session.
Parameters:
gameId (string): The game session ID
Returns:
Final game statistics
Move history
Completion status with congratulations messageles through systematic manipulation and real-time visualization.
Interactive Cube Manipulation: Execute standard Rubik's Cube moves (U, D, L, R, F, B and their variations)
Configurable Difficulty: Set scramble difficulty from 1-100 moves for varied challenge levels
MCP UI Integration: Interactive web components delivered directly from the MCP server with clickable game links
Game Session Management: Join existing games or create new ones with customizable settings
3D Real-time Visualization: Beautiful 3D cube visualization using Three.js and WebGL
WebSocket Live Updates: Real-time state synchronization between MCP server and web interface
Mouse Interaction: Rotate and examine the 3D cube with mouse controls
Recursive Workflow: AI agents can systematically work through cube solving using nextAction guidance
State Tracking: Complete move history and current cube state monitoring
Solution Detection: Automatic detection when the cube is solved with celebration effects
Related MCP server: Chess MCP Server
Node.js 18.x or higher
npm or yarn
cd rubiks-cube-mcp-server
npm installnpm run buildnpx rubiks-cube-mcp-serverThis will start both:
MCP server on stdio (for AI agent communication)
Web visualization server on http://localhost:3000
To use this MCP server with Claude Desktop, add the following to your claude_desktop_config.json:
{
"mcpServers": {
"rubiks-cube": {
"command": "npx",
"args": ["rubiks-cube-mcp-server"]
}
}
}Configuration file locations:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
After adding the configuration, restart Claude Desktop to load the MCP server.
startCubeInitialize a new Rubik's Cube game session.
Parameters:
scramble (optional, boolean): Whether to scramble the cube initially (default: true)
difficulty (optional, number): Number of scramble moves (1-100, default: 20)
Returns:
MCP UI resource with clickable game link
Game ID for the session
Initial cube state with difficulty level
Visualization URL
Next action guidance
joinGameJoin an existing Rubik's Cube game session.
Parameters:
gameId (string): The game session ID to join
Returns:
Current cube state
Game metadata including difficulty
Next action guidance
manipulateCubeExecute a move on the Rubik's Cube.
Parameters:
gameId (string): The game session ID
move (string): Standard cube notation (U, D, L, R, F, B, U', D', L', R', F', B', U2, D2, L2, R2, F2, B2)
Returns:
Updated cube state
Move execution confirmation
Total moves count
Next action guidance
finishComplete the Rubik's Cube game session.
Parameters:
gameId (string): The game session ID
Returns:
Final game statistics
Move history
Completion status
The server uses standard Rubik's Cube notation:
U: Up face clockwise
D: Down face clockwise
L: Left face clockwise
R: Right face clockwise
F: Front face clockwise
B: Back face clockwise
': Counter-clockwise (e.g., U')
2: Double turn (e.g., U2)
Agent: "Start a new Rubik's cube puzzle with easy difficulty"
→ startCube tool called with { scramble: true, difficulty: 5 }
→ Returns MCP UI resource with clickable game link + game state
Agent: "Join existing game cube_123456789_abc"
→ joinGame tool called with gameId
→ Returns current cube state and game metadata
Agent: "Execute move U"
→ manipulateCube tool called with move "U"
→ Returns updated state and nextAction guidance
Agent: "Continue solving..."
→ Recursive manipulateCube calls until solved
→ finish tool called when complete with celebration messageVisit http://localhost:3000/game/{gameId} to see:
Real-time 3D cube representation
Color-coded faces (White, Yellow, Red, Orange, Blue, Green)
Move counter and history
Interactive move buttons
Solution status indicator
The server now includes MCP UI integration for enhanced user experience:
Clickable Game Links: When starting a new game, the server returns an interactive UI resource with a clickable link to the web visualization
Game Session Management: Support for joining existing games created by other users or sessions
Visual Feedback: Clear indication of game status, difficulty level, and next actions
When you call the startCube tool, you'll receive:
A clickable UI resource linking directly to the game
Complete game state data in JSON format
Metadata including difficulty level and next action guidance
Use the joinGame tool with a game ID to participate in games created elsewhere:
Perfect for collaborative solving
Maintains full game state and history
Seamless integration with existing MCP workflow
MCP Protocol: Standard Model Context Protocol for AI agent communication
MCP UI Integration: Interactive web components with @mcp-ui/server for clickable resources
3D Rendering: Three.js WebGL-based 3D cube visualization
Real-time Communication: Socket.io WebSocket server for live updates
Web Server: Express.js server for HTTP API and static content
State Management: In-memory game session tracking with live synchronization
Configurable Difficulty: Scalable scramble complexity from beginner to expert levels
The server follows the recursive MCP pattern:
Start → Returns nextAction: 'manipulateCube'
Manipulate → Returns nextAction: 'manipulateCube' (if not solved) or 'finish' (if solved)
Finish → Returns nextAction: null (workflow complete)
This allows AI agents to work autonomously through the solving process.
npm run devnpm run buildsrc/
├── app.ts # Main MCP server setup
├── cubeLogic.ts # Rubik's Cube simulation logic
├── visualizationServer.ts # Web visualization server
└── types.ts # TypeScript interfacesMIT License - see LICENSE file for details.
Complete the Rubik's Cube game session
| Name | Required | Description | Default |
|---|---|---|---|
| gameId | Yes | The game session ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'completes' a game session, implying a mutation or finalization, but doesn't describe what 'complete' entails (e.g., saves results, ends gameplay, triggers scoring) or any side effects like permissions or rate limits. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a game completion tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens upon completion (e.g., returns a score, saves state, or provides confirmation), leaving the agent uncertain about the outcome or how to handle the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting the single required parameter 'gameId' as 'The game session ID'. The description adds no additional semantic meaning beyond this, such as format examples or constraints, so it meets the baseline for high schema coverage without compensating value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Complete') and the resource ('Rubik's Cube game session'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'joinGame' or 'manipulateCube', which might involve similar game sessions but different operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'startCube' or 'manipulateCube'. It lacks context about prerequisites (e.g., must be an active session) or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Join an existing Rubik's Cube game session
| Name | Required | Description | Default |
|---|---|---|---|
| gameId | Yes | The game session ID to join |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('join') but doesn't explain what happens upon joining (e.g., does it return game state, require authentication, have rate limits, or affect other players?). For a tool that likely involves multi-user interaction with no annotation coverage, this lack of behavioral context is inadequate, though not contradictory.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. There's zero waste, and every part of the sentence earns its place by clearly conveying the essential function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of joining a game session (likely involving multi-user state changes), the description is incomplete. No annotations exist to cover behavioral aspects like safety or side effects, and there's no output schema to explain return values (e.g., success confirmation or game details). The description alone doesn't provide enough context for an agent to understand the full implications of using this tool, especially compared to siblings like 'manipulateCube' or 'finish'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'gameId' fully documented in the schema as 'The game session ID to join'. The description doesn't add any meaning beyond this (e.g., format examples, source of the ID, or validation rules). With high schema coverage and only one parameter, the baseline score of 3 is appropriate, as the schema handles the heavy lifting without extra value from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('join') and resource ('an existing Rubik's Cube game session'), making the purpose immediately understandable. It distinguishes from sibling tools like 'startCube' (which creates a new game) and 'manipulateCube' (which interacts with an ongoing game), though it doesn't explicitly mention these alternatives. The description is specific but lacks explicit sibling differentiation, which keeps it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid game ID from 'startCube'), exclusions (e.g., cannot join a finished game), or contextual cues (e.g., use after starting a game). With sibling tools like 'finish' and 'manipulateCube' available, the absence of usage guidelines is a significant gap, leaving the agent to infer appropriate contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Execute a move on the Rubik's Cube
| Name | Required | Description | Default |
|---|---|---|---|
| gameId | Yes | The game session ID | |
| move | Yes | The cube move to execute |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'execute[s] a move,' implying a mutation or action, but doesn't clarify if this changes the cube state permanently, requires specific permissions, has side effects, or what happens on failure. This is a significant gap for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without any fluff or redundancy. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly, with every word earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation with no output schema and no annotations), the description is incomplete. It lacks information on behavioral traits, return values, error handling, and how it integrates with sibling tools, making it inadequate for an agent to use confidently without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with clear descriptions for both parameters ('gameId' and 'move'), including an enum for valid moves. The description adds no additional meaning beyond what the schema provides, such as explaining move notation or game session context, so it meets the baseline score of 3 when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('execute a move') and the target resource ('on the Rubik's Cube'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings like 'startCube' or 'finish', which likely handle different aspects of cube manipulation, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active game session from 'startCube' or 'joinGame'), exclusions, or how it relates to sibling tools like 'finish' for ending a session, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Initialize a new Rubik's Cube game session
| Name | Required | Description | Default |
|---|---|---|---|
| scramble | No | Whether to scramble the cube initially | |
| difficulty | No | Number of scramble moves (1-100) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool initializes a session but doesn't cover key aspects like whether this creates persistent state, requires authentication, has side effects, or returns session details, which are critical for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, earning full marks for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a game session tool with no annotations and no output schema, the description is incomplete. It fails to explain what the tool returns (e.g., session ID, cube state) or behavioral traits like side effects, leaving significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting both parameters. The description doesn't add any meaning beyond the schema, such as explaining how 'scramble' and 'difficulty' interact or default behaviors. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Initialize') and resource ('a new Rubik's Cube game session'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'joinGame' or 'manipulateCube', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'joinGame' or 'manipulateCube'. It lacks context about prerequisites or scenarios for starting a new session, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0joinGamestartCube1 field changedInput schema / properties / difficultyAdded value: +{
+ "description": "Number of scramble moves (1-100)",
+ "maximum": 100,
+ "minimum": 1,
+ "type": "number"
+}finishmanipulateCubestartCubeScored across 4 tools
Each tool has a clearly distinct purpose with no overlap: startCube initializes a game, joinGame connects to an existing one, manipulateCube performs moves, and finish ends the session. The actions are mutually exclusive and well-defined for the Rubik's Cube domain.
The naming is mixed with inconsistent patterns: startCube and joinGame use verbNoun format, manipulateCube uses verbNoun but with a different structure, and finish is a standalone verb. While readable, the lack of a uniform convention (e.g., snake_case or consistent verb placement) reduces predictability.
With 4 tools, this is well-scoped for a Rubik's Cube game server, covering essential actions: start, join, manipulate, and finish. Each tool earns its place without bloat, aligning with typical game lifecycle management.
The toolset covers core game operations (initialize, join, execute moves, end), but minor gaps exist, such as lacking tools for querying game state (e.g., get_cube_state) or listing active games. Agents can work around this by inferring state from context, but it's not fully comprehensive.
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