"Guidance on Dependency Checks and Latest Best Practices" matching MCP servers:

Enables scanning repositories for hardcoded service URLs and clients, and building service-to-service API dependency maps.

Enables coding agents to analyze Python source with AST-based static analysis, detect circular dependencies across monorepo packages via Tarjan SCC, and produce a topological build order with Kahn's algorithm along with refactoring plans and graph metrics. Runs with zero external dependencies over MCP from Claude Desktop, Cursor, or any compliant client.

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.

Provides comprehensive design principles and best practices to help LLMs generate modern, accessible web pages through guidance on layouts, colors, and typography. It enables users to review design approaches and access expert recommendations for responsive design, component structure, and current industry trends.

A Best Practices Oracle that provides dynamic advice, checklists, and architectural patterns for various software technologies. Helps developers with refactoring, testing guidelines, security checklists, and deployment principles through technology-aware recommendations.

MCP server providing interactive prompts for designing and reviewing microfrontend and microservice architectures, with embedded development rules and best practices.

Enables AI-powered threat modeling with tools for creating threat models, analyzing security threats, generating security controls, and validating architecture against best practices.

Creates, validates, and fixes diagrams on Eraser.io using their API. Supports sequence diagrams, flowcharts, cloud architecture diagrams, and entity relationship diagrams with automatic syntax error correction.

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

Enables generating, reading, auditing, and previewing BPMN 2.0 diagrams for Bizagi Modeler, with an automatic layout engine that produces files Bizagi can open, plus optional control of the Bizagi Modeler desktop app on Windows.

AI-native architecture diagramming for MCP clients (Claude Code, Cursor, Windsurf). The calling agent authors the graph (nodes, groups, edges); Flowgraf validates it, lays it out deterministically with ELK, renders an SVG + Mermaid, and returns a link to a live, editable canvas you can refine by chat, drag, or one-click AI design review. Agent-authored ops — no API key and no LLM cost to the calle

Enables AI coding agents to retrieve mode and stage guidance so they can lead users through a 9-stage design workflow, including questions, required artifacts, exit criteria, dependencies, pitfalls, rollback impact, and environment requirements. It helps non-designers turn ideas into buildable HTML/WPF design specs while keeping the human in control of confirmation and revisions.

Lets Claude Code, Cursor, VS Code and other AI agents draw and edit draw.io diagrams from your project's files, on a live browser canvas you can also edit by hand. Includes version history, undo, cloud shape libraries (AWS, Azure, GCP) and PNG or SVG export.

Renders diagram-as-code to PNG files on your disk, and also provides text-art previews and syntax validation, all locally without a browser or network.

Provides enterprise architecture knowledge tools that ground agents in curated patterns, enabling translation of messy enterprise asks into realistic architecture recommendations, platform selection, risk checks, and brand context retrieval.

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 two coding agents to deliberate on a plan in a shared room, taking turns to argue and converge until the lead writes a spec file and closes the room.

Provides design pattern templates and anti-pattern guidance to AI coding agents for correct pattern implementation.

Analyzes a local codebase and exposes its structure, per-file summaries, dependency graph, and complexity hotspots as tools for MCP clients like Claude.

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.