"Writing about MCP" matching MCP servers:

Generates GCP architecture diagrams, sequence diagrams, flow charts, and class diagrams using Python diagrams DSL via MCP.

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

An MCP server that lets AI agents drive FigJam boards through a local Figma plugin, bypassing API rate limits with 19 tools for reading, writing, and editing FigJam content.

Enables AI coding agents to make evidence-aware design-pattern decisions by analyzing cases, comparing options, detecting misuse, stress-testing assumptions, planning adoption, writing ADRs, and generating evidence plans with transparent scoring.

Enables AI assistants to understand and analyze Spring Boot codebases through static analysis, allowing natural language queries about endpoints, classes, dependencies, and architecture without running the application.

Enables AI agents to generate BYaML Architecture Graphs from evaluations, Terraform plans, and AWS scans, and to derive insights such as blast radius, cost summaries, and remediation plans without writing YAML.

Automatically generates mind map images from text content using Coze API workflow. Returns accessible image links that can be used in MCP-compatible tools like CodeBuddy, Cursor, and Qoder.

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.

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.

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

Enables streaming hand-drawn Excalidraw diagrams with smooth viewport camera control and interactive fullscreen editing.

Visual architecture canvas that updates in real-time. Agents can build, read, and modify system design diagrams — services, databases, queues, APIs, entities — all linked to actual code paths in your repo.

Enables AI agents to create, modify, and share diagrams on a live Excalidraw canvas through MCP tools, supporting shapes, text, arrows, batch operations, and export to shareable links with images.

A remotely-hosted MCP server that generates Azure architecture diagrams from agent-generated topology descriptions, with safe execution and consistent styling.

Enables generating GCP architecture, sequence, flow, and class diagrams using natural language or Python code via the diagrams library.

Converts quantum circuits into ZX-diagrams using categorical quantum mechanics, enabling circuit visualization, analysis, and optimization through deterministic gate mapping and rewrite rules.

An MCP server for AsyncAPI that enables parsing, validation, linting, conversion, model generation, and template generation from any MCP client using stdio.

This project integrates tldraw with Claude AI using the Model Context Protocol (MCP). It allows Claude to create and manipulate diagrams based on natural language instructions.

Enables AI agents to create, modify, and analyze diagrams using Draw.io (Diagrams.net) through MCP commands.

This enterprise MCP server template provides a production-ready, architecture-first foundation for building MCP servers in Python, with capability registry, dependency injection, and Docker support.