nano-tech-diagrams

name	nano-tech-diagrams
description	Create and edit tech diagrams using the nano-tech-diagrams MCP server (Nano Banana 2 via Fal AI). Supports text-to-image, image-to-image, whiteboard cleanup, and 28+ style presets.

Nano Tech Diagrams

This skill uses the nano-tech-diagrams MCP server to create and transform tech diagrams using Fal AI's Nano Banana 2 model.

MCP Server Location

Always use mcp__jungle-shared__nano-tech-diagrams__* (on ubuntuvm).

Do not use jungle-local. Its schema claims to accept local filesystem paths, but the process runs in an environment that cannot read the workstation's filesystem, so every local-path call fails with ENOENT. The shared instance plus the staging endpoint below is the supported path.

File Staging (CRITICAL)

The MCP server cannot read workstation file paths directly. For any tool that accepts an image_path parameter with a local file, stage it to the residence S3 (mcp-staging bucket) and pass the presigned URL as image_path — the MCP accepts http(s) URLs directly.

Staging workflow:

1. Upload the local file and get a presigned GET URL:

   URL=$(s3-stage /local/path/to/image.jpg)
   

2. Pass $URL as image_path to the MCP tool.
3. Objects auto-expire after 1 day (bucket lifecycle); presigned URL TTL defaults to 1 hour (--expires to override).

Batch staging:

For multiple files, call s3-stage for each (can be parallelised), collect the URLs, then call the MCP tools.

When staging is NOT needed:

• text_to_image — no input image required
• When image_path is already an http:// or https:// URL (Fal media, any public host)

Saving output to the workstation

The MCP returns a fal.media URL. Do not rely on the download_to parameter — it writes to the ubuntuvm process's filesystem, not the workstation. Download the returned URL yourself:

curl -sSL -o "/absolute/workstation/path/output.png" "<fal.media URL>"

Available Tools

Tool	Purpose
list_styles	Show all 28+ visual style presets (key, name, category, default aspect ratio)
list_diagram_types	Show all diagram type presets (network, flowchart, mind map, etc.)
whiteboard_cleanup	Clean up a whiteboard photo into a polished diagram
image_to_image	Transform an existing image into a styled tech diagram
text_to_image	Generate a diagram from a text description (no input image)

Defaults

• Model: Nano Banana 2 (baked in, not configurable)
• Resolution: 1K (default)
• Reasoning: Minimal (default)
• Output format: PNG
• Aspect ratio: auto (pass as parameter to override)

Workflow

For whiteboard cleanup:

1. Stage the image with s3-stage <path> to get a presigned URL
2. Optionally ask about style preference — default is clean_polished
3. Call whiteboard_cleanup with the presigned URL as image_path
4. If domain-specific terms are present, pass them as dictionary_words for accurate spelling
5. Download the returned fal.media URL to the workstation (see "Saving output" above)

For image-to-image transformation:

1. Stage the image with s3-stage <path> to get a presigned URL
2. Determine what transformation is needed: style change, diagram type conversion, or custom prompt
3. Call image_to_image with at least one of: prompt, style, or diagram_type, and the presigned URL as image_path
4. Common combos: style=blueprint + diagram_type=network_diagram
5. Download the returned fal.media URL to the workstation

For text-to-image generation:

1. Get the user's description of what diagram they want
2. Pick an appropriate diagram_type if it matches a preset
3. Pick a style if the user has a visual preference
4. Call text_to_image — no staging needed (no input image)
5. Download the returned fal.media URL to the workstation

Style Categories

• Professional: clean_polished, corporate_clean, hand_drawn_polished, minimalist_mono, ultra_sleek, blog_hero
• Creative: colorful_infographic, comic_book, isometric_3d, neon_sign, pastel_kawaii, pixel_art, stained_glass, sticky_notes, watercolor
• Technical: blueprint, dark_mode, flat_material, github_readme, photographic, terminal_hacker, visionary
• Retro & Fun: chalkboard, psychedelic, mad_genius, retro_80s, woodcut
• Language: bilingual_hebrew, translated_hebrew

Diagram Types

• Infrastructure: network_diagram, cloud_architecture, kubernetes_cluster, server_rack
• Software: system_architecture, microservices, api_architecture, database_schema
• Process: flowchart, decision_tree, sequence_diagram, state_machine, pipeline
• Conceptual: mind_map, wireframe, gantt_chart, comparison_table, org_chart

Notes

• For batch processing, call tools sequentially to avoid API rate limits
• The dictionary_words parameter helps with domain-specific terminology (e.g., ["Kubernetes", "Proxmox", "PostgreSQL"])
• Aspect ratio options: auto, 1:1, 4:3, 3:4, 16:9, 9:16, 3:2, 2:3, 21:9, 9:21
• Resolution options: 0.5K, 1K (default), 2K, 4K
• The mcp-staging S3 bucket has a 1-day object lifecycle; presigned URLs default to 1-hour TTL