"Exploring Applications of AutoGen Technologies" matching MCP servers:

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.

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

A Model Context Protocol server that gives an LLM a structured visual layer to describe what exists and get back a clean, precise SVG diagram instead of ASCII art.

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.

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.

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.

A read-only MCP server that gives AI agents access to Sparx Enterprise Architect models, enabling search, navigation, and reading of elements, packages, scenarios, and connectors from .qea exports without a running EA instance.

Enables converting ASCII and Unicode text diagrams into crisp, animated SVG with 1:1 verification, including repair of misaligned diagrams.

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.

Gives AI agents instant access to software architecture, dependencies, and impact analysis through pre-computed sgraph models, replacing dozens of grep/read cycles with a single tool call.

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.

A single, queryable source of engineering constraints that coding agents consult at code-generation time, exposed over an MCP server.

Render hierarchical system diagrams as PNGs from YAML definitions using a four-level ontology of networks, factories, machines, and nodes.

Enables MCP agents to validate architecture descriptions and scaffold complete, interactive React Flow diagram applications with multiple visual dialects, themes, exports, and verification probes.

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

MCP server for Umtri — give your AI coding agent a persistent map of your project's structure, dependencies, and bugs.

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.

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.

Gives terminal coding agents a local browser canvas for rendering charts, tables, metrics, markdown, live widgets and sandboxed MCP App UIs that would otherwise reach them as raw JSON. Lets agents pose blocking visual multiple-choice questions and read back the user's clicks, selections and an animated architecture map of file activity.

Enables AI agents to programmatically generate, edit, and view Excalidraw diagrams with real-time browser synchronization. It provides a suite of tools for adding shapes, text, and arrows to diagrams through natural language interactions.