Diagram generation for understanding codebases and system architecture is addressed by Blueprint MCP. It targets engineers and power users, leveraging Nano Banana Pro and integrating with Arcade's ecosystem (HubSpot, Google Drive, GitHub) to extract data and visualize it as architecture, sequence, or data flow diagrams, enhancing comprehension and documentation.

How It Works

Diagram generation is initiated via a job ID, with Nano Banana Pro processing code or documentation to produce diagrams in approximately 30 seconds. Users monitor progress and download the resulting PNG as base64. Its key advantage is integrating with Arcade tools to pull data from sources like HubSpot or Google Drive, enabling context-aware visualizations of system architecture, API flows, or data pipelines.

Quick Start & Requirements

• Primary Install: pip install arcade-mcp
• Prerequisites: Python 3, Arcade account (https://arcade.dev), Google AI Studio API key (https://aistudio.google.com/).
• Setup Steps: Sign up for Arcade, install CLI, login (arcade-mcp login), store API key (arcade-mcp secret set GOOGLE_API_KEY="your_api_key_here"), deploy server (cd architect_mcp && arcade-mcp deploy), create Arcade Gateway, and configure Cursor IDE.

Highlighted Details

• Generates detailed enterprise architecture diagrams, mapping layers from end-users to core banking infrastructure.
• Creates visual learning cards for complex architectures like LangGraph, detailing components and execution flows.
• Supports diverse diagram types: code architecture, API flows, process flowcharts, and data pipelines.
• Enables data extraction from external systems (HubSpot, Google Drive) for diagram context.

Maintenance & Community

No specific details regarding maintainers, community channels, or roadmap were found in the provided README content.

Licensing & Compatibility

The provided README content does not specify a software license. This lack of information may pose compatibility concerns for commercial use or integration into closed-source projects.

Limitations & Caveats

Adoption requires commitment to the Arcade platform and obtaining a Google AI Studio API key. Functionality is tied to the Arcade ecosystem and potentially specific IDE integrations like Cursor. The absence of explicit licensing information is a notable caveat.