"Using a Browser with Dev Tools to Debug a Web Application" matching MCP servers:

Provides UI architecture analysis for converting Figma designs or web pages into reusable UI code blocks with effort estimation in CSV format.

Turn natural language into 3D models in Fusion 360. 64 CAD tools including sketches, extrudes, fillets,and JIS standard parts.

Provides AI assistants with access to Apple's Human Interface Guidelines and technical API documentation across all Apple platforms (iOS, macOS, watchOS, tvOS, visionOS), enabling unified search of design principles and implementation details.

MCP server for rendering Mermaid diagrams and generating source-code diagrams, with tools to render text/files and produce dependency/class diagrams.

An MCP server that adds engineering discipline to AI-assisted development, enforcing evidence-gated TDD, security review, backup strategy, and deployment generation to turn AI-generated code into production-ready software.

Enables AI agents like Claude to interact with Figma designs through 50+ tools for creating, styling, and manipulating design elements, components, and variables via a WebSocket relay and Figma plugin.

Architecture-index MCP tools for kernelee apps that combine static analysis and runtime wiring into a JSON index, enabling coding agents to query control flow and dependencies via the Model Context Protocol.

An MCP server that enables AI assistants to interact with Figma designs for tasks like reading document info, creating elements, and managing auto layouts. It facilitates real-time design automation via a custom Figma plugin and WebSocket server integration.

Provides tools for AI-powered graph analysis, including relationship extraction, adjacency matrix creation, and network centrality calculations. It enables users to perform complex structural analysis and generate interactive D3.js visualizations from structured data.

Enforces a rigorous spec-driven engineering workflow for AI coding assistants, requiring requirements, design, and task planning before any code is written.

An MCP server that equips AI assistants with specialized, opinionated development playbooks for building microservices, frontends, databases, and DevOps pipelines. It integrates with clients like VS Code Copilot, Claude Desktop, and Cursor to provide battle-tested expertise.

Enables AI assistants to perform Electronic Design Automation (EDA) tasks including Verilog synthesis, simulation, ASIC design flows, and waveform analysis through a unified interface.

MCP server for creating and editing diagrams using draw.io. Allows generating diagrams from Mermaid or XML, searching shapes, and opening them in draw.io for export.

Enables coding agents to write repository documents (READMEs, RFCs, design docs, ADRs) from verified codebase facts, using a separate model for drafting and agent fact-checking for accuracy.

Connects AI coding agents to Circuitry's visual workflow platform, enabling them to create and sync code nodes from project files, understand user-drawn flowcharts and diagrams, generate visual flowcharts, and create data visualizations like spreadsheets and charts.

Enables AI agents to visualize tasks on a collaborative Sketchbord whiteboard by composing content into diagrams, editing them incrementally, and reading back the board including user-drawn additions.

We built a hosted MCP server that gives AI agents two capabilities through a single connection: 1. img-forge — Image generation across 5 quality tiers (SDXL Lightning to Gemini 3.1 Flash). One tool call, 5-30 seconds, done. 2. Stackbilder — Full-stack architecture scaffolding. Describe a product, get a 6-mode pipeline (Product → UX → Risk → Architect → TDD → Sprint)

Enables AI agents to query and control the Unity Editor, supporting scene management, GameObject manipulation, asset browsing, play mode control, and real-time editor operations through 52+ tools.

Enables interactive MATLAB development by allowing users to execute scripts and specific code sections, manage workspace variables, and capture generated plots. It integrates with the MATLAB Python Engine to provide persistent execution context for MCP-compatible clients.

Enables AI-powered threat modeling with tools for creating threat models, analyzing security threats, generating security controls, and validating architecture against best practices.