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Provides automated UX laws analysis across multiple platforms and tools.
Configuration
View docs{
"mcpServers": {
"agencia-tecnologica-multiverse-limitada-ux-ui-mcp": {
"command": "node",
"args": [
"C:/ruta/a/UX-UI-MCP/dist/index.js"
]
}
}
}You can analyze and audit UX interfaces across multiple platforms using a single MCP server. It automatically detects the target platform, applies platform-specific patterns, and provides a suite of analysis tools to evaluate how well a design adheres to UX laws and heuristics.
To use the MCP server, run it and connect with your MCP client. You can perform a full audit against all UX laws or target specific patterns for a given platform. The server will analyze the provided code and return actionable insights, checklists, and cross-platform comparisons to help you improve usability.
Prerequisites: Node.js (version 14.x or newer) and npm. Make sure Node is available in your environment before proceeding.
npm install
npm run buildYou can configure the MCP server in your desktop client by adding the following MCP server entry. This runs the server locally using Node and the compiled index file.
{
"mcpServers": {
"ux_laws": {
"command": "node",
"args": ["C:/ruta/a/UX-UI-MCP/dist/index.js"]
}
}
}The MCP server automatically detects the platform from the code you supply, or you can specify it directly. You gain access to per-platform patterns, a collection of 37 tools, and dedicated checklists for faster, more consistent UX improvements.
Keep your Node.js environment updated and review access controls for any MCP client connections. Regularly rebuild when dependencies change to ensure you are using the latest platform patterns and UX rules.
If the server fails to start, verify that Node is installed, the path to the compiled dist/index.js is correct, and that your client is configured to connect to the local stdio server as shown.
Analyzes the Fitts's Law pattern by evaluating target sizes and distances to predict interaction efficiency.
Assesses decision complexity by evaluating the number of choices and required effort to reach an action.
Measures familiarity and ease of use by checking common interaction patterns and conventions.
Evaluates memory load by considering the number of items a user must retain (7±2 rule).
Checks tolerance and robustness in input handling following Postel’s Law.
Analyzes user experience by focusing on the peak moments and the end of interactions.
Assesses how aesthetic quality impacts perceived usability and effectiveness.
Evaluates response times to ensure interactions stay under optimal thresholds.
Measures irreducible complexity and the amount of information a user must process.
Identifies 80/20 patterns to prioritize essential UI elements and interactions.
Examines grouping cues to improve visual harmony and comprehension.
Assesses grouping based on shared regions to reduce cognitive load.
Applies Gestalt principles to streamline perception and interpretation.
Evaluates similarity to convey consistent meaning and reduce confusion.
Checks how evenly elements are connected visually to guide attention.
Ensures incomplete shapes still convey a complete idea, improving interpretation.
Assesses how related items share a common trajectory or outcome.
Analyzes how elements guide the eye along a smooth path.
Distinguishes foreground vs background to improve readability.
Evaluates ordering effects, such as primacy and recency, on perception.
Detects anomaly effects where distinct items stand out and affect recall.
Accounts for motivation differences when tasks are interrupted.
Assesses grouping of information into manageable chunks to reduce load.
Measures overall mental effort required to process a UI task.
Evaluates how well the UI directs user focus to critical elements.
Analyzes progress indicators and feedback to smooth user motivation.
Simplifies design choices to reduce unnecessary complexity.
Considers how latency affects user expectations and patience.
Controls information exposure to manage complexity over time.
Provides timely feedback to confirm user actions and outcomes.
Performs a comprehensive audit across all 30 UX laws for a given component.
Retrieves detailed information for a specific UX law across platforms.
Lists all UX laws, with optional category filtering.
Generates a platform-specific checklist for a component type.
Lists all supported platforms with their detection patterns.
Detects the platform based on provided code or file extension.
Compares how a law applies across multiple platforms.