"Cloud Infrastructure Management and Deployment Tools for Oracle Cloud and A2A Communication" matching MCP servers:

Provides cloud architecture analysis, recommendations, and artifacts (diagrams, ADRs, deployment comparisons) for any project, supporting AWS, GCP, and Azure.

Enables visualization of Terraform plan changes as interactive cloud architecture diagrams with official AWS, Azure, and GCP icons, showing resource dependencies and changes.

Enables stateless querying of PostgreSQL databases, inspecting RabbitMQ queues, and generating PlantUML diagrams through MCP, with credentials supplied dynamically via client headers.

Enables planning AWS architectures, reviewing plans, and provisioning resources after administrative approval with durable execution tracking.

Analyzes software projects to extract architecture, build dependency graphs, and predict the impact of code changes.

Provides tools for AI-powered graph analysis, including relationship extraction, adjacency matrix creation, and network centrality calculations. It enables users to perform complex structural analysis and generate interactive D3.js visualizations from structured data.

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.

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

Architecture-index MCP tools for kernelee apps that combine static analysis and runtime wiring into a JSON index, enabling coding agents to query control flow and dependencies via the Model Context Protocol.

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.

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

Enables AI assistants to perform Electronic Design Automation (EDA) tasks including Verilog synthesis, simulation, ASIC design flows, and waveform analysis through a unified interface.

Enables creation of infrastructure and architecture diagrams as code using the Python diagrams library, supporting 15+ cloud providers, 500+ node types, custom icons, and flowcharts with multiple output formats.

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 assistants to visualize cloud architecture diagrams, generate and import Terraform HCL, and manage infrastructure resources directly from chat through the CloudForge platform.

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.

Enables generating cloud architecture diagrams, flowcharts, sequence diagrams, and more using three rendering engines: mingrammer/diagrams, Mermaid, and PlantUML.

Enables LLMs to model, validate, and analyze multi-cloud infrastructure as a typed graph, with tools for IaC import/export, cost estimation, and architecture review.

Enables interactive MATLAB development by allowing users to execute scripts and specific code sections, manage workspace variables, and capture generated plots. It integrates with the MATLAB Python Engine to provide persistent execution context for MCP-compatible clients.

Validates and renders declarative JSON diagram specs to themeable SVG. The format has no coordinates, so a model writes structure and the renderer does the layout; tools: validate, render, kinds.

Offline MCP server for SAP ABAP static analysis, ABAP Cloud readiness scoring, and RAP scaffolding. It enables AI agents to lint ABAP source, compare reworks, check released APIs, and generate RAP business objects without needing an SAP system.

MCP server for creating and editing diagrams using draw.io. Allows generating diagrams from Mermaid or XML, searching shapes, and opening them in draw.io for export.

15 AI-powered UML diagram tools for coding agents. Generates class, sequence, state, ER, threat model, deployment and architecture diagrams in Mermaid syntax. Works in Claude Code, Cursor and Windsurf.

Enables rendering, validation, formatting, and inspection of D2 diagrams via the Model Context Protocol, using WASM for rendering without requiring the d2 binary.

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.

Enables LLMs to search and retrieve official Cisco network diagram icons as RGB PNG images, with metadata and category listing tools for building topology diagrams.

Provides systems thinking models as composable analysis lenses for architecture, infrastructure, DevOps, incident analysis, and technical decision-making.

Enables coding agents to write repository documents (READMEs, RFCs, design docs, ADRs) from verified codebase facts, using a separate model for drafting and agent fact-checking for accuracy.

An MCP server that builds a local webpage to view AI plans, reports, and diagrams, so the AI only needs to send a URL pointer instead of long text. It provides three tools (view_plan, view_report, view_diagram) and tracks project changes for diff viewing.

Model Context Protocol (MCP) server for @imqueue — lets AI coding agents (Claude Code, Cursor and others) search the docs, scaffold typed services & clients and use @imqueue/cli live.