"React Query" 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.

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.

Enables AI agents to query organizational architecture and governance constraints, returning evidence-grounded answers from documented structures.

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.

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.

Mneme exposes a governed Decision Index so MCP clients can propose candidate architectural decisions and query decision state, applicability, and traceability. Proposals remain non-authoritative: accepting or activating protections stays under explicit human control.

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.

An MCP server that exposes a Svelte/SvelteKit project's component dependency graph over stdio, enabling AI coding assistants to query component imports, unused components, and route dependencies without an editor.

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

Enables an AI assistant to load, query and edit a YAML or JSON graph file, with tools for adding, editing and removing nodes and edges, managing reusable styles and graph-level properties, and saving changes. Every change is written to the file immediately, so the same graph can be viewed and edited live in the companion web app.

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

Enables AI assistants to read and write ArchiMate models stored in CoArchi XML format. Query elements, create relationships, design diagrams, and sync changes to Git through natural language.

Enables AI to analyze, query, and manage a graph-based representation of software architecture for impact analysis, dependency tracking, and design.

Enables AI assistants to interact with Autodesk Revit to query project data, manage elements, and execute generated code via the Model Context Protocol. It provides full compatibility with GitHub Copilot and Claude to automate BIM modeling workflows.

Grafema builds a queryable knowledge graph of your codebase and allows you to enforce structural invariants and query the system using Datalog or Cypher.

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.

MCP bridge to live SysML v1 models in CATIA Magic / Cameo Systems Modeler (No Magic MSoSA). Lets Claude Code or any MCP agent query, audit, and edit MBSE models — blocks, requirements, diagrams, parametrics, traceability — over a local, air-gapped connection.

Enables AI agents to query architecture context, data contracts, and blast radius to prevent cross-repo architectural breakage before merging.

Living typed knowledge graph for software projects, exposed over MCP so coding assistants can capture and query modules, capabilities, flows, events, rules and decisions across sessions. SQLite-backed, schema-validated, ships as a Claude Code plugin.

Enables read-only access to Sparx Systems Enterprise Architect repositories stored in various database systems via ODBC, allowing AI assistants to browse and query model data without requiring Windows or a running EA instance.