"Tools for embedding React and React Native in Android native applications" matching MCP servers:

An MCP server designed for React Native and Expo development that provides specialized tools for project scaffolding, architectural best practices, and troubleshooting. It enables AI assistants to guide users through setup, navigation configuration, and CI/CD processes using modern stacks like NativeWind and Zustand.

Enables AI agents to analyze and scaffold React/Next.js applications enforcing Feature-Sliced Design (FSD) conventions, providing tools for project analysis, rule retrieval, and entity generation.

Provides React design and rendering patterns from patterns.dev as MCP tools and resources for Claude Code.

Enables AI assistants to deeply analyze and visualize React and React Native codebases locally through 36 free MCP tools for component trees, complexity scoring, navigation, data flow, health audits, and interactive tracing.

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.

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

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.

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.

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

Enables users to create, validate, view, and export system stock-and-flow maps from a versioned JSON model through MCP-capable hosts over local stdio or hosted Streamable HTTP. Supports causal-loop and nested-level mapping while keeping submitted model content with the caller and requiring no LLM provider key.

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 that provides a live, terminal-native layered dependency map for AI coding assistants, with tools to track and visualize development progress in real time.

Enables MCP agents to validate architecture descriptions and scaffold complete, interactive React Flow diagram applications with multiple visual dialects, themes, exports, and verification probes.

Semantic React/TSX analysis MCP server that saves 70-90% tokens by using AST to retrieve precise component usages, prop flow, and state update information for AI coding assistants.

An MCP server that lets agents draw 18 diagram types from JSON (no SVG, no headless browser)

Sub-1ms cross-stack AST contract layer and compiler verification engine mapping React/Next.js routes to FastAPI and SQLAlchemy models for AI coding agents.

A local-first MCP server for macOS that enables AI assistants to read and manage Apple Calendar events via EventKit, with configurable permissions, audit logging, and a native setup app.

MCP server for foldkit that exposes 7-prime spine, 7 κ-bands, and 6 fold operations as native tools and resources for use in MCP clients like Claude Code, enabling state folding, κ-band classification, and fold operations.

Enables autonomous software engineering workflows by routing intent to specialized modes, managing Fable5 task ledgers and backend contracts, auditing React/TypeScript stacks, generating architectural SVG diagrams, and enforcing write-guard path policies.

Enables AI coding agents to create and iteratively edit native Ipe vector figures for academic papers via natural language, with transactional batches, stable object IDs, LaTeX-measured text, and native undo in the live GUI.