"JavaScript programming language resources" matching MCP servers:

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

Enables auto-configuration and validation of React components against a glassmorphic design token system using an AST correction engine. It supports managing UI presets, enforcing design uniformity in Monaco IDE, and exporting tokens as CSS, Tailwind, or JavaScript variables.

MCP server for AI Diagram Maker — generate software engineering diagrams from natural language, code, ASCII diagram, images, or Mermaid. Inline diagram rendering using MCP apps UI and diagram URL in responses. Works with Cursor, Claude Desktop, Claude Code, and any MCP-compatible AI.

Enables Claude Desktop and other MCP clients to list, read, export, and create Cloudcraft cloud-architecture blueprints, as well as snapshot AWS resources.

Generates professional architecture diagrams from natural language descriptions using template-driven prompts and swappable AI image providers.

Distills Claude Code's 310K-line source into 32 queryable modules via MCP, enabling AI agents to learn and reuse Claude Code's architectural patterns through natural language.

MCP server for comprehensive code analysis, navigation, and quality assessment across 25+ programming languages.

MCP server for generating and editing architecture diagrams from natural language or code, supporting formats like Terraform, docker-compose, Kubernetes, SQL, Mermaid, and PlantUML.

Generate and render PlantUML diagrams from natural language. A pure Node.js MCP server that creates, validates and explains UML diagrams (sequence, class, activity, state, component and more) as SVG — with zero Java and zero external server. Tools: render_diagram, check_syntax, explain_diagram. Just run npx @plantuml/mcp-js.

Enables AI hosts to generate editable online diagrams (flowcharts, mindmaps, UML, and more) from natural language or Mermaid, using a ProcessOn account via the Model Context Protocol.

Enables AI assistants to directly control Autodesk 3ds Max through natural language to create models, set materials, adjust lighting, and automate animations. It bridges the Model Context Protocol with 3ds Max via a TCP socket to execute Python and MAXScript commands.

Generates editable Excalidraw diagrams from natural language system descriptions, with properly bound arrows and labels. Includes tools for diagram creation, validation, and backend status.

Local code-graph engine for AI coding workflows: static analysis of Rust, Cangjie, ArkTS, TypeScript/JavaScript, C/C++, Python, and Shell projects into symbols, imports, call graphs, and quality gates, with pre-commit change review and impact analysis. Read-only by design — never executes build scripts or uploads code.

Enables AI assistants to generate professional UML diagrams (class, use case, activity, sequence) from natural language descriptions, producing editable .drawio files compatible with diagrams.net.

Enables AI agents to programmatically generate, edit, and view Excalidraw diagrams with real-time browser synchronization. It provides a suite of tools for adding shapes, text, and arrows to diagrams through natural language interactions.

Enables AI assistants to create and validate workflow diagrams using FlowZap's text-based DSL. Generates shareable playground URLs for visualizing flowcharts, process diagrams, and CI/CD pipelines through natural language descriptions.

Enables creating CORAS risk and threat diagrams from natural-language descriptions, producing .dgx files that the SINTEF Threat Modelling Tool opens natively, including layout, validation, and rendering.

MCP server for repository mapping, dependency analysis, and architecture diagram generation for JavaScript, TypeScript, and Python projects.

Generates draw.io diagrams and architecture designs from natural language prompts using DrawX API, integrating with Claude, Cursor, and VS Code.

Enables AI assistants to understand and analyze Spring Boot codebases through static analysis, allowing natural language queries about endpoints, classes, dependencies, and architecture without running the application.