"Architecture for automating quality assurance with services" matching MCP servers:

An MCP server that generates standalone SVG architecture diagrams from text descriptions, running entirely on your machine with no dependencies or network access.

Provides architecture design expertise to AI coding agents, analyzing requirements, selecting architecture patterns, generating concrete designs, and evaluating quality attributes.

Scans AWS environments and generates professional architecture diagrams showing VPC networking, compute, storage, and security resources.

An agnostic MCP server that reads arc.yaml from the workspace, exposing tools to map layers, trace slices, generate scaffolding, and validate architectural rules.

Enables scanning Java/Maven projects to generate TOGAF-standard architecture deliverables (Excel and PPTX) via natural language commands.

Enables agents and IDEs to generate and verify NestJS microservices with hexagonal architecture, JSON:API contracts, and mandatory security headers. Supports declarative spec-based module generation, refactoring existing services, quality checks, and per-repository inventory and auditing.

Compare evidence-linked documentation claims with facts observed in the current source tree.

Enables scaffolding and managing Clean Architecture in Next.js projects, providing tools to initialize structure, create features with all layers, and validate architecture compliance.

Analyzes GitHub and local repositories to automatically generate visual architectural diagrams such as dependency graphs, class diagrams, and data flow diagrams.

Analyzes Java Spring Boot Maven repositories by scanning source code, building a dependency graph, and exposing tools for architecture overview, change impact, dependency cycles, rule validation, and refactoring targets so LLMs can answer architecture questions without rereading the codebase.

An MCP server for evaluating C# project architecture quality using the Modularity Maturity Index (MMI) framework. It provides tools for detecting layering violations, circular dependencies, and encapsulation issues with interactive D3.js visualizations.

Enables users to translate geometric bounding boxes, flowchart node connections, and architectural sketches into clean Mermaid graphs, JSON topology matrices, and boilerplate code scaffolds through MCP.

Enables translation of geometric bounding boxes, flowchart node connections, and architectural sketches into clean Mermaid graphs, JSON topology matrices, and boilerplate code scaffolds.

Enables MCP-compatible AI agents to read and write architecture-map projects and diagrams with per-project access controls via OAuth 2.1/PKCE.

Generates tailored system architecture recommendations based on business parameters like QPS, concurrent users, database type, and AI model size, providing resource allocation plans, middleware suggestions, and exportable architecture diagrams.

Generates, reviews, and imports cloud architecture diagrams for AWS, Azure, and Google Cloud from editable specs, Terraform, or live Google Cloud inventory, rendering them as PNG, SVG, PDF, or JPG.

Enables AI agents to discover and work with a user's permitted Excalidraw boards through a single MCP endpoint, reading and adding elements, images, and snapshots while respecting owner, view, edit, and guest-link access controls.

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 generating editable draw.io architecture diagrams from system descriptions, with automatic ELK layout, official icons, layered views, and objective quality scoring.

Enables AI agents to create publication-quality scientific diagrams, flowcharts, and architecture diagrams in OmniGraffle via natural language commands.