"Understanding HTTP Requests" matching MCP servers:

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

Stop pasting your file tree into Claude. Give any AI assistant real architectural understanding of a codebase — local, private, zero‑config.

Enables MCP clients to list, select, create, summarize, and edit ExcaliDash (Excalidraw) drawings through the Drawing Agent API, supporting both stdio and Streamable HTTP transport.

Model Context Protocol server that lets AI agents drive StarUML programmatically — generate UML diagrams, execute commands, and manage elements and projects via HTTP.

Local MCP server that converts modeling exercise requests into native Astah projects (.asta), supporting multiple UML diagram types with automatic layout and visual validation.

Enables agents to analyze codebases (local or GitHub) and automatically generate Mermaid diagrams rendered as PNG images via Kroki, providing visual understanding of project structure and flow through file discovery, reading, and diagram generation.

Builds a semantic graph of codebases across 38 languages and exposes 42 MCP tools for structured code understanding, search, and impact analysis.

Provides AI agents with a live architecture model of a codebase, enabling queries for root cause analysis, blast radius, and dependency traversal through MCP tools.

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.

Provides tools for creating, deleting, and querying nodes and edges in Excalidraw diagrams, enabling diagram editing via LLM interfaces.

An MCP server that integrates CST Studio Suite with the Model Context Protocol to enable automated electromagnetic simulation workflows. It provides specialized tools for material definition management and direct interaction with the CST Studio Suite environment.

Provides comprehensive architectural expertise through specialized agents, resources, and tools for generating, evaluating, and modifying architectural designs.

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.

An MCP server that generates and manages nifdi diagrams as SVG files, bundled with skills that teach models in depth, placement grammar, and build workflow through natural language.

Enables AI agents to read, explain, lint, and edit existing BPMN 2.0 files in a repository while preserving diagram layout and structural integrity through parsed-document patch operations.

MCP server enabling AI agents to design and deploy WRedis/Redis-backed services using expert patterns, architecture scaffolding, and a unified CLI.

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

Enables visual collaboration with an AI agent on a codebase through a shared drawing canvas, where hand-drawn diagrams are inferred as editable structure over MCP.

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

The Fabric-Analytics-MCP server enables AI agents to interact directly with Microsoft Fabric using natural language. It transforms complex data engineering tasks—such as workspace management, data exploration, and job execution—into intuitive, conversational workflows for LLMs like Claude or GitHub