"Plotly Dash - A Python Framework for Building Interactive Web Dashboards" matching MCP servers:

Exposes the 23 Gang of Four design patterns to AI coding agents for generation, canonical examples, AST-based detection, validation, and anti-pattern refactoring in Python codebases.

Connects Claude Desktop to BULC fire simulation software for AI-powered building design, enabling natural language creation of rooms, walls, and multi-story structures with spatial awareness and undo/redo support.

A Model Context Protocol server for deep codebase understanding of Python projects, focusing on data analysis and scientific computing. It provides architectural analysis, pattern detection, dependency mapping, test coverage analysis, and AI-optimized context generation.

Translates natural language commands into structured geometric operations for a simulated CAD engine using LLMs. It enables users to create shapes, modify dimensions, and perform 3D operations like extrusion through the Model Context Protocol.

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

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 designs software projects by drafting design documents with an LLM, refining them, answering questions, and creating projects via the AI2DEV API.

An MCP server that enables AI agents to manage STAR-pattern architecture diagrams, creating, updating, listing, and building interactive viewers via tool calls.

MCP server for the Product Framework that enables agents to author and verify a What/How graph, with a live web view for visualizing the domain model, event flows, and system maps.

This enterprise MCP server template provides a production-ready, architecture-first foundation for building MCP servers in Python, with capability registry, dependency injection, and Docker support.

Generates GCP architecture diagrams, sequence diagrams, flow charts, and class diagrams using Python diagrams DSL via MCP.

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 rendering, validation, formatting, and inspection of D2 diagrams via the Model Context Protocol, using WASM for rendering without requiring the d2 binary.

Cloud infrastructure provisioning via natural language. Enables deploying production-ready infrastructure on AWS, GCP, Azure, or Oracle with a single prompt.

Enables LLMs to search and retrieve official Cisco network diagram icons as RGB PNG images, with metadata and category listing tools for building topology diagrams.

Provides systems thinking models as composable analysis lenses for architecture, infrastructure, DevOps, incident analysis, and technical decision-making.

A Model Context Protocol server that gives an LLM a structured visual layer to describe what exists and get back a clean, precise SVG diagram instead of ASCII art.

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.

An MCP server that builds a local webpage to view AI plans, reports, and diagrams, so the AI only needs to send a URL pointer instead of long text. It provides three tools (view_plan, view_report, view_diagram) and tracks project changes for diff viewing.

🐍 🏠 - Code graph for AI agents over MCP: resolves Python and TypeScript calls to fully qualified names and reports the share it could not resolve instead of guessing. Multi-hop impact analysis, authz reachability audit, architectural drift against declared patterns. Local, SQLite. uvx codegraph-brain