"Managing Vercel Projects and Their Integrations" matching MCP servers:

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.

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 auto-configuration and validation of React components against a glassmorphic design token system using an AST correction engine. It supports managing UI presets, enforcing design uniformity in Monaco IDE, and exporting tokens as CSS, Tailwind, or JavaScript variables.

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 creating, managing, analyzing, and visualizing knowledge graphs with support for multiple graph types (topology, timelines, changelogs, requirements, knowledge bases, ontologies) including node/edge management and resource association.

Connects Claude directly to Godot 4 projects to read and manipulate scenes, nodes, scripts, and assets within the editor. It enables real-time scene tree management, script editing, and resource configuration through a local Node.js bridge and GDScript plugin.

Local-first MCP server for storing and managing project architecture, modules, data flow, and usage examples with complete privacy.

Local code-graph engine for AI coding workflows: static analysis of Rust, Cangjie, ArkTS, TypeScript/JavaScript, C/C++, Python, and Shell projects into symbols, imports, call graphs, and quality gates, with pre-commit change review and impact analysis. Read-only by design — never executes build scripts or uploads code.

MCP server for automatic technical documentation generation of Satrack projects.

An MCP server that recommends tech stacks for your project. Describe what you're building and get a recommended stack with reasoning, tradeoffs, and what each layer should use.

Enables users to turn ideas or PRDs into component selections and architecture designs, audit existing projects with static scans, and manage long-running planning/auditing tasks with caching, cancellation, budget tracking, and checkpoint resume via MCP tools.

MCP server for repository mapping, dependency analysis, and architecture diagram generation for JavaScript, TypeScript, and Python projects.

The Diagrams.so MCP server enables generating, editing, and managing cloud architecture diagrams from any MCP client, wrapping the public Diagrams.so API.

MCP server that creates, edits and exports architecture diagrams as .fluyo.json files, operating through tools like create_diagram, edit_diagram, and export_diagram directly from Claude.

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 an AI assistant to load, query and edit a YAML or JSON graph file, with tools for adding, editing and removing nodes and edges, managing reusable styles and graph-level properties, and saving changes. Every change is written to the file immediately, so the same graph can be viewed and edited live in the companion web app.

Turns Claude or ChatGPT into a live system design interviewer that watches a hand-drawn whiteboard, reads the diagram as structured data or an image, hears spoken answers, pins questions on components, and grades the session. Everything runs locally, so users can practice mock interviews on their own machine without API keys.

Serves reusable SDLC agent roles and review checklists over MCP, enabling AI coding agents to execute structured product analysis, solution architecture, code review, and release management tasks in GitHub-first projects.

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