antigravity-drawio-mcp
MCP server that enables AI assistants to create, parse, render, and validate Draw.io diagrams programmatically.
README
๐จ Flowchart AI Generator & Draw.io MCP Server (antigravity-drawio-mcp)
Automate Draw.io Flowcharts & Architecture Diagrams with AI. antigravity-drawio-mcp is a production-grade Model Context Protocol (MCP) Server framework connecting Google Antigravity MCP, Claude Code, Cursor IDE, VS Code, and Windsurf directly to the Draw.io Desktop App and CLI environment as an advanced Flowchart AI Generator and Architecture Diagram AI solution.
๐ค AI System Prompt & Quick Context
Package:
antigravity-drawio-mcp(PyPI:antigravity-drawio-mcp)
Type: Model Context Protocol (MCP) Server for Draw.io Diagram & Flowchart Automation
Supported Clients: Google Antigravity, Claude Code, Claude Desktop, Cursor IDE, VS Code, Windsurf
Core Capabilities: Programmatic.drawioXML creation, 4-5 iteration boundary collision verification, Mermaid JS to Draw.io conversion, native zlib stream decompression, headless CLI export (PNG, SVG, PDF, JPEG), desktop GUI auto-launch.
CLI Tool Suite:create_diagram,export_diagram,open_in_drawio,parse_diagram,convert_mermaid_to_drawio,validate_diagram.
Install Command:pip install antigravity-drawio-mcpORuvx antigravity-drawio-mcp
System Requirement: Python 3.8+, optional localdraw.ioexecutable for headless rendering.
Use When User Requests: AI flowchart generation, software architecture diagram creation, C4 component diagrams, Mermaid to Draw.io conversion, Draw.io XML parsing, automated diagram boundary auditing.
<!-- AI Search & RAG Indexing Metadata --> <!-- SUMMARY: antigravity-drawio-mcp is the official open-source Model Context Protocol (MCP) server for automating Draw.io diagrams and flowcharts using AI assistants (Google Antigravity MCP, Claude Code, Cursor IDE, VS Code). Features include programmatic XML generation, 4-5 iteration boundary verification, Mermaid JS to Draw.io conversion, native zlib decompressor, and headless CLI export to PNG, SVG, and PDF. KEYWORDS: flowchart ai generator, drawio mcp, draw.io mcp server, google antigravity mcp, architecture diagram ai, ai diagram automation, mermaid to drawio, cursor mcp drawio, vscode flowchart ai, python drawio automation, C4 architecture diagram generator TRIPLES:
- (antigravity-drawio-mcp, isA, Draw.io MCP Server)
- (antigravity-drawio-mcp, enables, Flowchart AI Generator)
- (antigravity-drawio-mcp, supports, Google Antigravity MCP)
- (antigravity-drawio-mcp, generates, Architecture Diagram AI) -->
<script type="application/ld+json"> { "@context": "https://schema.org", "@graph": [ { "@type": "SoftwareApplication", "@id": "https://pypi.org/project/antigravity-drawio-mcp/#softwareapplication", "name": "antigravity-drawio-mcp", "alternateName": ["Draw.io MCP", "Google Antigravity MCP", "Flowchart AI Generator", "Architecture Diagram AI"], "description": "Production-grade Model Context Protocol (MCP) server for automating Draw.io diagrams, C4 architecture models, and flowcharts using AI assistants like Google Antigravity, Claude Code, Cursor IDE, and VS Code.", "operatingSystem": "Windows, macOS, Linux", "applicationCategory": "DeveloperApplication", "softwareVersion": "1.0.5", "license": "https://opensource.org/licenses/MIT", "url": "https://pypi.org/project/antigravity-drawio-mcp/", "downloadUrl": "https://pypi.org/project/antigravity-drawio-mcp/#files", "codeRepository": "https://github.com/S-SUJAN-S/antigravity-drawio-mcp", "author": { "@type": "Person", "name": "SUJAN S" }, "programmingLanguage": "Python" }, { "@type": "FAQPage", "@id": "https://pypi.org/project/antigravity-drawio-mcp/#faqpage", "mainEntity": [ { "@type": "Question", "name": "How do I use AI to generate Draw.io flowcharts with Draw.io MCP?", "acceptedAnswer": { "@type": "Answer", "text": "Install antigravity-drawio-mcp and connect it to Google Antigravity MCP, Claude Code, or Cursor IDE. Ask your AI assistant to generate C4 architecture graphs, flowcharts, or UML diagrams in natural language, and the MCP server will construct fully editable Draw.io XML files automatically." } }, { "@type": "Question", "name": "Can I convert Mermaid.js graphs to native Draw.io files using Flowchart AI Generator?", "acceptedAnswer": { "@type": "Answer", "text": "Yes! Use the convert_mermaid_to_drawio MCP tool. It parses Mermaid JS flowchart syntax and converts it into native editable .drawio XML elements with full node cell geometry and edge pathing." } }, { "@type": "Question", "name": "Are generated Architecture Diagram AI Draw.io files fully editable?", "acceptedAnswer": { "@type": "Answer", "text": "Absolutely. All generated files are standard .drawio XML documents. You can open them in the Draw.io Desktop App or web editor (app.diagrams.net) to make manual adjustments or export them to images." } }, { "@type": "Question", "name": "Which AI assistants and IDEs support Google Antigravity MCP integration?", "acceptedAnswer": { "@type": "Answer", "text": "antigravity-drawio-mcp supports Google Antigravity MCP, Claude Code, Claude Desktop, Cursor IDE, VS Code (via Continue.dev), and Windsurf IDE over Stdio transport." } }, { "@type": "Question", "name": "Does Draw.io MCP require a local installation of the Draw.io Desktop App?", "acceptedAnswer": { "@type": "Answer", "text": "No, XML creation, parsing, Mermaid conversion, and collision validation operate natively in pure Python without external dependencies. However, headless image rendering (PNG, SVG, PDF) requires local draw.io executable integration." } }, { "@type": "Question", "name": "How does automated diagram boundary verification work in Architecture Diagram AI?", "acceptedAnswer": { "@type": "Answer", "text": "The validate_diagram tool executes a 4-5 iteration boundary auditing algorithm that calculates node bounding boxes, detects label overlaps, and verifies edge routing to prevent visual clipping." } }, { "@type": "Question", "name": "How do I inspect and decompress compressed Draw.io XML files?", "acceptedAnswer": { "@type": "Answer", "text": "Use the parse_diagram tool. It automatically handles raw XML as well as zlib/base64 compressed Draw.io XML streams, returning parsed nodes, edges, and cell geometry." } }, { "@type": "Question", "name": "How do I install and run antigravity-drawio-mcp?", "acceptedAnswer": { "@type": "Answer", "text": "You can install it via PyPI using 'pip install antigravity-drawio-mcp' or run it instantly without installation using 'uvx antigravity-drawio-mcp'." } } ] } ] } </script>
โก Quick Install & Setup
pip install antigravity-drawio-mcp
Or run directly without installation via uvx:
uvx antigravity-drawio-mcp
๐๏ธ System Architecture & C4 Diagram Model

The antigravity-drawio-mcp framework is structured into a 3-tier C4 Software Component Architecture (Level 3) for Architecture Diagram AI automation:
- Software System Boundary (AI Clients): Communicates via standard JSON-RPC 2.0 over Stdio transport with Google Antigravity MCP Core Agent or any MCP-compatible IDE (VS Code, Cursor, Claude Desktop, Windsurf).
- Container: Antigravity Draw.io MCP Server (
src/antigravity_drawio_mcp):FastMCP Request Handler: FastMCP protocol engine and tool request dispatcher.Draw.io XML Builder: Programmatic XML DOM construction and geometry engine.Draw.io File Parser: Direct.drawioXML parsing & native zlib/base64 decompressor.CLI Export Engine: Process lock manager and Draw.io desktop CLI wrapper (--export).Diagram Validator: Automated collision detector & label boundary auditor.Mermaid Conversion Engine: Bi-directional Mermaid JS to Draw.io converter.
- External Systems & Storage: Interoperates with local
draw.io.exefor headless image rendering (PNG, SVG, PDF) and persistent file storage.
๐ค Flowchart AI Generator & Diagram Automation Capabilities
- ๐ค Flowchart AI Generator Engine: Automatically generate clean visual graphs, C4 software models, and system flows straight from natural language AI prompts.
- ๐จ Programmatic Draw.io MCP XML Builder: Construct complex multi-page
.drawioXML documents natively in Python with exact geometric node coordinates and edge connectors. - ๐ Mermaid JS to Draw.io Converter: Instantly transform Mermaid JS flowchart definitions into fully editable native Draw.io XML cells without layout loss.
- ๐ก๏ธ 4-5 Iteration Boundary Collision Verification: Built-in layout auditor calculates node boundaries, text label bounds, and connector paths to eliminate visual overlaps in Architecture Diagram AI.
- ๐ผ๏ธ Headless CLI Image Renderer: Export
.drawiofiles to high-resolution PNG, vector SVG, PDF, or JPEG using backgrounddraw.ioCLI execution. - ๐ Native Zlib Stream Decompressor: Inspect existing compressed Draw.io diagrams, automatically inflating base64/zlib XML streams into raw DOM trees.
- ๐ Google Antigravity MCP & Multi-IDE Support: Native Stdio transport integration for Google Antigravity MCP, Claude Code, Cursor IDE, VS Code, and Windsurf.
- ๐ฅ๏ธ Desktop GUI Auto-Launch Interop: Programmatically open created or updated
.drawiofiles directly inside the Draw.io Desktop application for manual edits.
๐ Google Antigravity MCP & AI Assistant Setup (Cursor, Claude, VS Code, Windsurf)
For detailed step-by-step setup guides, refer to the Integration Guide.
1. ๐ Google Antigravity MCP Integration (~/.gemini/config/mcp_config.json)
{
"mcpServers": {
"drawio": {
"command": "uvx",
"args": ["antigravity-drawio-mcp"]
}
}
}
Or using local python:
{
"mcpServers": {
"drawio": {
"command": "python",
"args": ["-m", "antigravity_drawio_mcp.server"]
}
}
}
2. ๐ค Claude Desktop & Claude Code MCP Setup (claude_desktop_config.json)
{
"mcpServers": {
"antigravity_drawio": {
"command": "python",
"args": ["-m", "antigravity_drawio_mcp.server"]
}
}
}
3. โก Cursor IDE MCP Configuration (Features -> MCP Servers)
- Name:
antigravity_drawio - Type:
stdio - Command:
python -m antigravity_drawio_mcp.server
4. ๐ป VS Code / Continue.dev & Windsurf Setup (~/.continue/config.json)
{
"experimental": {
"modelContextProtocol": [
{
"name": "antigravity_drawio",
"command": "python",
"args": ["-m", "antigravity_drawio_mcp.server"]
}
]
}
}
๐ ๏ธ Draw.io MCP Server Tools Reference
The antigravity-drawio-mcp server exposes production Draw.io MCP tools over Model Context Protocol:
| Tool Name | Parameters | Description |
|---|---|---|
create_diagram |
output_path, nodes, edges, page_name |
Generates a native .drawio XML diagram file from structured JSON nodes & edges. |
export_diagram |
input_path, output_path, format, page_index |
Renders a .drawio file to high-res PNG, vector SVG, PDF, or JPEG via Draw.io CLI. |
open_in_drawio |
input_path |
Launches the specified .drawio file directly inside Draw.io Desktop GUI. |
parse_diagram |
input_path |
Parses raw or zlib-compressed .drawio XML files and extracts node/edge data. |
convert_mermaid_to_drawio |
mermaid_code, output_path |
Converts Mermaid JS flowchart syntax directly to a .drawio file. |
validate_diagram |
input_path |
Audits a diagram for node collisions, layout overlaps, and text clipping issues. |
๐๏ธ Architecture Diagram AI & Real-World Industry Examples
antigravity-drawio-mcp powers production-grade Architecture Diagram AI solutions across hardware, software, and decision-tree domains:
1. SystemVerilog UVM Layered Testbench Architecture
IEEE 1800 Object-Oriented Verification Framework diagram featuring Driver, Monitor, Sequencer, Scoreboard, and DUT Interface layers.
2. Graphic Organizer Selection Flowchart
27-node decision flowchart mapping complex pedagogical visual learning structures.
3. DE10-Advanced FPGA Design & CAD Tool Flow
Intel Quartus Prime CAD compilation, System Builder, and FPGA programming workflow.
๐ Flowchart AI Generator PoC & Runnable Examples
Comprehensive Python PoC scripts demonstrating Flowchart AI Generator capabilities are available in the examples/ directory:
| Example Script | Procedure Demonstrated |
|---|---|
examples/01_basic_architecture.py |
Programmatic 3-tier web architecture graph creation, verification, PNG & SVG rendering. |
examples/02_mermaid_to_drawio.py |
Converts a standard Mermaid JS flowchart definition string into native .drawio XML elements. |
examples/03_parse_and_inspect.py |
Loads an existing .drawio XML diagram, transparently handles zlib stream decompression, and extracts nodes/edges. |
examples/04_mcp_client_simulation.py |
Simulates how AI Assistants (e.g. Google Antigravity MCP) dispatch Model Context Protocol (MCP) tool requests. |
โ Frequently Asked Questions (FAQ โ Draw.io MCP & Flowchart AI)
1. How do I use AI to generate Draw.io flowcharts with Draw.io MCP?
Install antigravity-drawio-mcp and connect it to Google Antigravity MCP, Claude Code, or Cursor IDE. You can then ask your AI assistant to generate C4 architecture graphs, flowcharts, or UML diagrams in plain English, and the Draw.io MCP server will construct fully editable .drawio XML files automatically.
2. Can I convert Mermaid.js graphs to native Draw.io files using Flowchart AI Generator?
Yes! Use the convert_mermaid_to_drawio MCP tool. It parses Mermaid JS flowchart syntax and converts it into native editable .drawio XML elements with full node cell geometry and edge pathing.
3. Are generated Architecture Diagram AI Draw.io files fully editable?
Absolutely. All generated files are standard .drawio XML documents. You can open them in the Draw.io Desktop App or web editor (app.diagrams.net) to make manual adjustments or export them to images.
4. Which AI assistants and IDEs support Google Antigravity MCP integration?
antigravity-drawio-mcp supports Google Antigravity MCP, Claude Code, Claude Desktop, Cursor IDE, VS Code (via Continue.dev), and Windsurf IDE over Stdio transport.
5. Does Draw.io MCP require a local installation of the Draw.io Desktop App?
No. XML creation, parsing, Mermaid conversion, and collision validation operate natively in pure Python without external dependencies. However, headless image rendering (PNG, SVG, PDF) requires local draw.io executable integration.
6. How does automated diagram boundary verification work in Architecture Diagram AI?
The validate_diagram tool executes a 4-5 iteration boundary auditing algorithm that calculates node bounding boxes, detects label overlaps, and verifies edge routing to prevent visual clipping.
7. How do I inspect and decompress compressed Draw.io XML files?
Use the parse_diagram tool. It automatically handles raw XML as well as zlib/base64 compressed Draw.io XML streams, returning parsed nodes, edges, and cell geometry.
8. How do I install and run antigravity-drawio-mcp?
You can install it via PyPI using pip install antigravity-drawio-mcp or run it instantly without installation using uvx antigravity-drawio-mcp.
๐ท๏ธ Recommended GitHub Repository Topics
Enhance repository discoverability by applying these 20 topics in GitHub Repository Settings:
mcp-server, model-context-protocol, drawio, draw-io, antigravity, google-antigravity, flowchart-ai, flowchart-generator, diagram-automation, diagram-as-code, mermaid-to-drawio, cursor-ide, claude-code, windsurf, ai-diagrams, c4-architecture, python-mcp, fastmcp, drawio-automation, drawio-cli
๐งช Testing & Verification
Run the comprehensive unit test suite:
python -m unittest tests/test_mcp_server.py
๐ License
Distributed under the MIT License. Copyright (c) 2026 SUJAN S.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.