"PWA" matching MCP servers:

Routes one brief to the right image model across 60+ (gpt-image-1.5, Ideogram 3, Recraft V4, Flux), validates the output, and fans out to iOS/Android/PWA/favicon/visionOS/Flutter bundles. Works without an API key via Pollinations, HF Inference, Stable Horde, or host-LLM inline SVG.

Enables AI assistants to generate, edit, and deploy production-ready full-stack applications through VULK's automated development pipeline. It supports multi-file code generation, browser verification, and exports to web, PWA, and mobile platforms.

Generate deployment-ready PWA, iOS, and Android app icon sets from a text description. Produces all 27 required sizes, maskable icons, Xcode-ready iOS icons, Android mipmap folders, splash screens, and manifest.json packaged as a ZIP. Powered by Google Imagen 4.

Enables local-first model routing and persistent tool library management, allowing automated workflow detection and conversion of stable patterns into reusable tools.

Enables agents to run statistics and data-science computations over numerical streams using only the Python standard library, including Z-score/IQR anomaly detection, Holt linear forecasting, Welch's t-test hypothesis evaluation, gradient-descent multivariate regression, and power-iteration SVD/PCA dimensionality reduction. Exposes these capabilities over JSON-RPC 2.0 stdio so clients like Claude Desktop, Cursor, and Windsurf can project high-dimensional feature vectors into principal components without any external dependencies.

Enables Claude to receive physical touch events from a phone via the PWA and respond with text, haptic vibrations, and expression changes, giving an AI companion embodied presence through touch.

Enables agents to run zero-dependency statistical analysis natively over MCP, including Power Iteration PCA/SVD dimensionality reduction, Holt linear forecasting, modified Z-score and Tukey IQR anomaly detection, Welch's t-test, and multivariate gradient-descent regression on numerical data streams. Projects high-dimensional feature vectors into principal component representations without any external libraries.

Enables comprehensive audit of WhatsApp business conversations, including history export, LLM analysis with verification, and multi-format report generation.

An MCP server that converts Windows WPR .etl performance traces into structured JSON summaries and flamegraph-ready data for LLM analysis. It bridges Windows Performance Analyzer automation with LLM reasoning capabilities for performance troubleshooting.

A self-hosted HTTP MCP server wrapping the ElevenLabs speech-to-text API, enabling audio transcription with speaker diarization.

Provides tools to validate SageMaker workloads against the six pillars of the AWS Well-Architected Framework, returning findings with severity levels and recommendations.