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io.github.dengyu123456/crochet-engine

Deterministic photo-to-crochet-chart engine: stitch counts, 5 techniques, yarn estimates.

Media & ImagesPythonv0.1.1

crochetpatterngen-engine

The deterministic photo-to-crochet-chart engine behind crochetpatterngen.com — packaged as a Python library, CLI, and MCP server so AI agents (Claude Desktop, Cursor, etc.) can turn photos into crochet charts with exact stitch counts.

Deterministic, not generative. There is no AI image generation here — just resize, median-cut color quantization, and confetti cleanup. Same input, same chart, same stitch counts, every time. No hallucinated rows.

Why this engine

  • Real stitch counts — every chart comes with per-color hex + stitch counts that sum exactly to the grid size. What you see is what you crochet.
  • C2C block aspect correction — C2C blocks are physically wider than tall (0.7:1 h:w). The engine adjusts grid dimensions so the worked piece keeps the photo's proportions instead of coming out squashed.
  • 5 technique presets — graph, c2c, tapestry, mosaic, filet.
  • Yarn estimation — per-color yardage for 6 yarn weights (fingering → super bulky).
  • Zero heavy deps — Pillow + numpy only. Optional rembg extra for background removal.

Install

pip install crochetpatterngen-engine          # core
pip install crochetpatterngen-engine[mcp]     # + MCP server
pip install crochetpatterngen-engine[rembg]   # + background removal

Python API

from PIL import Image
from crochet_chart_engine import generate_chart, render_design, estimate_yarn

png_bytes, meta = generate_chart(
    Image.open("photo.jpg"),
    technique="c2c",     # graph | c2c | tapestry | mosaic | filet
    grid_w=60,           # 20..120
    n_colors=8,          # 2..16
)
# meta: {"grid_w", "grid_h", "colors": [{"hex", "count"}],
#        "total_stitches", "technique", "warning"}

yarn = estimate_yarn(meta, weight="worsted")
# {"total_yards": ..., "colors": [{"hex", "count", "yards"}], ...}

png_bytes, meta = render_design("designs/frog.txt")  # ASCII design -> chart

CLI

crochet-chart chart photo.jpg out.png --technique c2c --grid-w 60 --colors 8
crochet-chart design designs/frog.txt frog.png
crochet-chart yarn photo.jpg --technique graph --weight worsted

MCP server (Claude Desktop & friends)

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "crochet": {
      "command": "uvx",
      "args": ["--from", "crochetpatterngen-engine[mcp]", "crochetpatterngen-mcp"]
    }
  }
}

Or with a regular pip install:

{
  "mcpServers": {
    "crochet": {
      "command": "python",
      "args": ["-m", "crochet_chart_engine.mcp_server"]
    }
  }
}

Tools exposed (stdio transport):

ToolWhat it does
photo_to_chartLocal image path → chart PNG (base64 or saved to output_path) + per-color stitch counts JSON
render_ascii_designASCII design file → chart PNG + stitch counts
estimate_yarn_toolStitch counts → per-color yardage for one yarn weight or all

ASCII design format

See designs/frog.txt and designs/dragon.txt:

# comment
palette: G=#58A05C, W=#FFFFFF, .=#FAFAF7
title: Frog Face
technique: graph
---
..GGGG..........GGGG....
.GGWWGG........GGWWGG...

One character per stitch; . is the background/padding color. Rows are padded to the longest row.

Development

pip install -e .[dev,mcp]
pytest tests/

License

MIT — see LICENSE.


Free web tool + pattern library at crochetpatterngen.com.

Installation

Source-derived launch command. Check the maintainer’s required arguments and credentials before running:

bash
uvx crochetpatterngen-engine

Set up in your AI client

Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.

json
{
  "mcpServers": {
    "io-github-dengyu123456-crochet-engine": {
      "command": "uvx",
      "args": [
        "crochetpatterngen-engine"
      ]
    }
  }
}

Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.

Claude Desktop setup reference

Package

crochetpatterngen-enginepypi

Compatible MCP Clients

io.github.dengyu123456/crochet-engine works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

  • Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.
  • Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.
  • VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.
  • Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.
  • Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

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