Skip to main content
Glama
Sign In
io.github.dengyu123456/crochet-engine

io.github.dengyu123456/crochet-engine

by dengyu123456
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

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.

Related MCP server: ASCII & SVG Art Studio

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):

Tool

What it does

photo_to_chart

Local image path → chart PNG (base64 or saved to output_path) + per-color stitch counts JSON

render_ascii_design

ASCII design file → chart PNG + stitch counts

estimate_yarn_tool

Stitch 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.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    This server cannot be deployed

    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    Resources

    Related MCP Connectors

    Related MCP Servers

    • texel-mcp

      Brunovncs
      A
      license
      A
      quality
      B
      maintenance
      Enables AI agents to create, validate, review, patch, save, share, and preview Minecraft textures and skins by compiling JSON specs deterministically to PNG, with review sheets, art feedback, docs, examples, and workspace-safe file operations.
      14
      77 npm
      1
      MIT

    • dither-mcp

      lennrt
      A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to inspect images, compare and apply 41 dithering algorithms with 256 curated or custom palettes, and produce stills, animations, video, and print separations locally while saving reusable recipes. It exposes these image-processing workflows through typed MCP tools, resources, and prompts, keeping source files and artifacts in a user-controlled workspace.
      MIT

    Appeared in Searches