This tool isn’t really needed given that there are multiple websites, where you can upload your collection and your deck, and they will tell you exactly which cards in the deck are missing from your collection.

For example:

• Archidekt — collection tracker + deck builder
• Moxfield — modern deck builder with collection support
• Deckstats — deck-building + collection management
• Deckbox — collection manager that shows missing cards for a deck
• ManaBox — app for collection tracking + deck building
• MTGGoldfish — has features to input your collection and compare against decks
• Untapped.gg — for MTG Arena, tells you which decks you can build given your collection

So while a custom format legality checker is neat, if your goal is simply “which cards do I lack in this deck given my collection”, one of those sites will do just fine.

• Commander with low power brackets, no tutors, no infinite combos, and mostly budget decks.

• Cube Draft.

• Playing precons against the computer using Forge. I copy the names of the precons from a block, then play them against each other using a bit of randomization:

import itertools, random

decks = ["Deck A", "Deck B", "Deck C", ...]
matchups = list(itertools.combinations(decks, 2))
random.shuffle(matchups)

for i, (deck1, deck2) in enumerate(matchups, 1):
    print(f"Match {i}: {deck1} vs {deck2}")

• Aside from the usual Theme Decks, some of the most interesting precons are Duel Decks, Pro Tour Collector Sets, Salvat 2005 and 2011, and Commander decks. You can find a full list of precon decks here.
• Penny Dreadful on MTGO when I want constructed but cheap play.
• I've played a bunch of Draft and Standard on MTG Arena but I didn't really enjoy it that much. It felt like a chore doing the dailies and just caring about getting the four wins per day.

I really used to like classic cards like Serra Angel and Shivan Dragon and I don't know exactly when they became so bad, but I couldn't even consider playing them now in most formats.

I believe Throne of Eldraine in 2019 was the set where power creep started accelerating most.

I've managed to write another script that seems to work:

import json
import re

def load_legal_cards(json_file):
    """
    Load legal cards from a JSON file with structure:
    { "sets": [], "cards": [], "banned": [] }
    """
    with open(json_file, 'r', encoding='utf-8') as f:
        data = json.load(f)
    legal_cards = [card.lower() for card in data.get('cards', [])]
    banned_cards = [card.lower() for card in data.get('banned', [])] if 'banned' in data else []
    return legal_cards, banned_cards

def clean_line(line):
    """
    Remove quantities, set info, markers, and whitespace
    Skip lines that are section headers like 'Deck', 'Sideboard'
    """
    line = re.sub(r'^\d+\s*x?\s*', '', line)  # "2 " or "2x "
    line = re.sub(r'\(.*?\)', '', line)        # "(SET)"
    line = re.sub(r'\*\w+\*', '', line)        # "*F*"
    line = line.strip()
    if re.match(r'^(deck|sideboard)\s*:?\s*$', line, re.IGNORECASE):
        return None
    return line if line else None

def validate_deck(deck_file, legal_cards, banned_cards):
    """
    Returns a list of illegal cards
    """
    illegal_cards = []
    with open(deck_file, 'r', encoding='utf-8') as f:
        lines = f.readlines()

    for line in lines:
        card_name = clean_line(line)
        if not card_name or card_name.startswith("#"):
            continue  # skip empty or comment lines

        card_lower = card_name.lower()
        if card_lower in banned_cards or card_lower not in legal_cards:
            illegal_cards.append(card_name)

    return illegal_cards

def main():
    legal_cards_file = 'legal_cards.json'   # JSON with "cards" and optional "banned"
    decklist_file = 'decklist.txt'          # Your decklist input

    legal_cards, banned_cards = load_legal_cards(legal_cards_file)
    illegal_cards = validate_deck(decklist_file, legal_cards, banned_cards)

    if illegal_cards:
        print("Illegal cards:")
        for card in illegal_cards:
            print(card)

if __name__ == "__main__":
    main()

I exported the Standard Penny collection from Moxfield to JSON using a Python script:

import csv
import json

input_csv = 'moxfield_haves_2025-10-21-1123Z.csv'
output_json = 'standard_penny.json'

sets = set()
cards = []

with open(input_csv, newline='', encoding='utf-8') as csvfile:
    reader = csv.DictReader(csvfile)
    for row in reader:
        name = row.get('Name')
        edition = row.get('Edition')
        if name:
            cards.append(name)
        if edition:
            sets.add(edition.upper())

sets = sorted(list(sets))

output_data = {
    "sets": sets,
    "cards": cards
}

with open(output_json, 'w', encoding='utf-8') as jsonfile:
    json.dump(output_data, jsonfile, indent=2)

print(f"JSON saved to {output_json}")

I saved the JSON file as validator/formats/standardpenny.json and added it to the validator’s config:

{ "name": "Standard Penny", "key": "standardpenny", "datafile":"formats/standardpenny.json" },

Then I tried to validate this deck exported as Plain Text from Moxfield and got the error.

When I try to validate a deck, I only see the message “Loading data, please wait…” and nothing happens. So I’m not sure if it’s a problem with my JSON export, the file path, or the validator itself.

No, it's just for reference.

Seems simple enough, so I'm going to try and make one myself. Here's the idea I have so far:

1. User selects a default format or uploads a JSON list of legal cards.
2. User pastes decklist text or uploads deck JSON.
3. Script compares deck entries with legal list.
4. Output = list of illegal cards.

I’m not aware of a single tool, but you could ensure the deck is standard legal in any normal deck building tool, then additionally check it against the Penny Dreadful deck checker - if it passes both, it should be legal in your format (assuming I understand what you’re doing correctly.)

Edit: Nevermind, I see you’re limiting it to $1, not $0.01, despite borrowing the name. Penny Dreadful checker won’t work.

Yeah Penny Dreadful uses tix<=0.02 and this uses both tix<=0.1 and usd<=1

✅ This will create a fully Moxfield-compatible CSV with all cards from a Scryfall search.

import requests
import csv
import time

QUERY = "f:standard f:penny usd<=1"
BASE_URL = "https://api.scryfall.com/cards/search"
PARAMS = {
    "q": QUERY,
    "unique": "cards",
    "format": "json"
}

OUTPUT_FILE = "moxfield_import.csv"

FIELDNAMES = [
    "Count",
    "Tradelist Count",
    "Name",
    "Edition",
    "Condition",
    "Language",
    "Foil",
    "Tags",
    "Last Modified",
    "Collector Number",
    "Alter",
    "Proxy",
    "Purchase Price"
]

def fetch_all_cards():
    url = BASE_URL
    params = PARAMS.copy()
    while True:
        resp = requests.get(url, params=params)
        resp.raise_for_status()
        data = resp.json()
        for card in data.get("data", []):
            yield card
        if not data.get("has_more"):
            break
        url = data["next_page"]
        params = None
        time.sleep(0.2)

def write_cards_to_csv(filename):
    with open(filename, "w", newline="", encoding="utf-8") as f:
        writer = csv.DictWriter(f, fieldnames=FIELDNAMES)
        writer.writeheader()
        for card in fetch_all_cards():
            row = {
                "Count": 1,
                "Tradelist Count": "",
                "Name": card.get("name"),
                "Edition": card.get("set"),
                "Condition": "",
                "Language": card.get("lang"),
                "Foil": "Yes" if card.get("foil") else "No",
                "Tags": "",
                "Last Modified": "",
                "Collector Number": card.get("collector_number"),
                "Alter": "",
                "Proxy": "",
                "Purchase Price": ""
            }
            writer.writerow(row)

if __name__ == "__main__":
    write_cards_to_csv(OUTPUT_FILE)
    print(f"Saved all cards to {OUTPUT_FILE}")

My first try was using this script:
Query Scryfall + dump card names out for easy import into Moxfield

❯ python scryfall_search.py -q "f:standard f:penny usd<=1" --output-as-file "$HOME/desktop/out.csv"
Running Scryfall search on f:standard f:penny usd<=1 legal:commander
Found 1,197 total matches!

But when I tried importing the output csv in Moxfield, I got a bunch of No card name found on line x errors.

The list needs to be static. How can you create decks for a format that is constantly changing? What I need is a way to share a consistent list of legal cards so that everyone can search within the same list, rather than each person having a different version.

Are you answering to the right post?

Forge not only has all the decks with their original printings but also has the capability to play against the AI.

You can either go here https://mtg.wtf/deck Or the same data is also exported to mtgjson if you want it in JSON format https://mtgjson.com/ The same data is also available in a few other export formats.

Source data for it is in https://github.com/taw/magic-preconstructed-decks with source URLs for every deck (some of these expired by now and you'd need to go to the Web Archive - WotC redesigns its website every few years, killing old URLs).

Inferring exact set and collector number based on all available information is done algorithmically.

Everything should have correct names, quantities, and set codes.

A few cards won't have correct collector numbers. The list of cards which are generally expected to not have exact collector number: "Plains", "Island", "Swamp", "Mountain", "Forest", "Wastes", "Azorius Guildgate", "Boros Guildgate", "Dimir Guildgate", "Golgari Guildgate", "Gruul Guildgate", "Izzet Guildgate", "Orzhov Guildgate", "Rakdos Guildgate", "Selesnya Guildgate", "Simic Guildgate"

For everything else, the algorithm is exact as far as we know. Anything the algorithm can't detect automatically it flags, and we resolve it manually.

— Tomasz Wegrzanowski

I noticed that the default deck download format on the website doesn't include set code and collector number information.

If you're fine with JSON, you can use mtgjson, or this file: https://raw.githubusercontent.com/taw/magic-preconstructed-decks-data/master/decks_v2.json (which is exported to mtgjson).

In case it matters, collector numbers are Gatherer-style not Scryfall-style (so DFCs are 123a / 123b, not 123 etc.). This only really affects cards with multiple parts.

Do you have any more questions?

— Tomasz Wegrzanowski

You can download the .txt file for each decklist from MTGGoldfish by clicking on the "Download > Exact Card Versions (Tabletop)" button. However, please note that these files may not be compatible with Xmage due to differences in formatting. Nonetheless, creating a conversion script should not be too difficult.

https://github.com/taw/mtg

mtg

Magic the Gathering scripts.

scripts

• analyze_deck_colors - reports colors of the deck according to correct algorithm [ http://t-a-w.blogspot.com/2013/03/simple-and-correct-algorithm-for.html ]
• clean_up_decklist - clean up manually created decklist
• cod2dck - convert Cockatrice's .cod to XMage's .dck
• cod2txt - convert Cockatrice's .cod to .txt format
• txt2cod - convert plaintext deck formats to Cockatrice's cod
• txt2dck - convert plaintext deck format to XMage
• txt2txt - convert plaintext deck format to plaintext deck format (i.e. normalize the decklist)
• url2cod - download decklists from URL and convert to .cod (a few popular websites supported)
• url2dck - download decklists from URL and convert to XMage .dck format
• url2txt - download decklists from URL and convert to .txt format

data management

These are used to generate data in data/, you probably won't need to run them yourself

• generate_colors_tsv_mtgjson - generate data/colors.tsv from mtgjson's AllSets-x.json (recommended)
• generate_colors_tsv_cockatrice - generate data/colors.tsv from cockatrice's cards.xml (use mtgjson instead)
• mage_card_map_generator - generate data/mage_cards.txt

Here are step-by-step instructions to migrate decks_v2.json to .dck files with the desired structure, assuming no prior knowledge of the command line:

1. Open a web browser and go to the following link: https://github.com/taw/magic-preconstructed-decks
2. Click the green "Code" button and select "Download ZIP" to download the repository as a ZIP file.
3. Extract the ZIP file to a folder on your computer.
4. Open the folder and create a new file migrate_decks.py.
5. Right-click on the file and select "Open With" and then choose a text editor such as Notepad or Sublime Text.
6. Copy the following Python script and paste it into the text editor:

import json
import os
import re

from typing import List, Dict

DECKS_FOLDER = 'Preconstructed Decks'

def load_decks(file_path: str) -> List[Dict]:
    with open(file_path, 'r') as f:
        return json.load(f)

def format_deck_name(name: str) -> str:
    name = name.lower().replace(' ', '_').replace('-', '_')
    return re.sub(r'[^a-z0-9_]', '', name)

def get_deck_info(deck: Dict) -> Dict:
    return {
        'name': format_deck_name(deck['name']),
        'type': deck['type'],
        'set_code': deck['set_code'].upper(),
        'set_name': deck['set_name'],
        'release_date': deck['release_date'],
        'deck_folder': DECKS_FOLDER,
        'cards': deck['cards'],
        'sideboard': deck['sideboard']
    }

def build_deck_text(deck_info: Dict) -> str:
    lines = [
        f'// {deck_info["name"]}',
        f'// Set: {deck_info["set_name"]} ({deck_info["set_code"]})',
        f'// Release Date: {deck_info["release_date"]}',
        '',
    ]

    for card in deck_info['cards']:
        lines.append(f'{card["count"]} [{card["set_code"]}:{card["number"]}] {card["name"]}')

    lines.append('')
    lines.append('SB:')

    for card in deck_info['sideboard']:
        lines.append(f'{card["count"]} [{card["set_code"]}:{card["number"]}] {card["name"]}')

    return '\n'.join(lines)

def build_deck_path(deck_info: Dict) -> str:
    return os.path.join(deck_info['deck_folder'],
                        deck_info['type'],
                        deck_info['set_code'])

def write_deck_file(deck_info: Dict, deck_text: str) -> None:
    deck_path = build_deck_path(deck_info)
    os.makedirs(deck_path, exist_ok=True)

    filename = f"{deck_info['name']}.dck"
    file_path = os.path.join(deck_path, filename)

    with open(file_path, 'w') as f:
        f.write(deck_text)

def migrate_decks(input_file: str, error_file: str) -> None:
    decks = load_decks(input_file)

    error_decks: List[Dict] = []
    for deck in decks:
        try:
            deck_info = get_deck_info(deck)
            deck_text = build_deck_text(deck_info)
            write_deck_file(deck_info, deck_text)
        except KeyError:
            error_decks.append(deck)

    if error_decks:
        with open(error_file, 'w') as f:
            json.dump(error_decks, f)

if __name__ == '__main__':
    migrate_decks('decks_v2.json', 'error_decks.json')

1. Open a terminal or command prompt on your computer. On Windows, you can do this by pressing the Windows key and typing "cmd" and then pressing Enter.
2. Navigate to the folder where the decks_v2.json file and the migrate_decks.py file are located. You can do this by typing cd followed by the path to the folder, such as cd C:\Users\YourName\Downloads\magic-preconstructed-decks-master.
3. Type python migrate_decks.py and press Enter to run the Python script.
4. Wait for the script to finish running. It will create a .dck file for each deck in the decks_v2.json file, with the desired structure.

Note: If you don't have Python installed on your computer, you can download it from the official website: https://www.python.org/downloads/. Choose the latest version for your operating system and follow the installation instructions.

https://github.com/taw/magic-preconstructed-decks-data

This repository contains machine readable decklist data generated from:

• https://github.com/taw/magic-preconstructed-decks
• https://github.com/taw/magic-search-engine

Files

decks.json has traditional cards + sideboard structure, with commanders reusing sideboard.

decks_v2.json has cards + sideboard + commander structure. You should use this one.

Data format

Data file i a JSON array, with every element representing one deck.

Fields for each deck:

• name - deck name
• type - deck type
• set_code - mtgjson set code
• set_name - set name
• release_date - deck release date (many decks are released much after their set)
• cards - list of cards in the deck's mainboard
• sideboard - list of cards in the deck's sideboard
• commander - any commanders deck has (can be multiple for partners)

Each card is:

• name - card name
• set_code - mtgjson set card is from (decks often have cards from multiple sets)
• number - card collector number
• foil - is this a foil version
• count - how many of given card
• mtgjson_uuid - mtgjson uuid
• multiverseid - Gatherer multiverseid of card if cards is on Gatherer (optional field)

Data Limitations

All precons ever released by Wizards of the Coast should be present, and decklists should always contain right cards, with correct number and foiling, and mainboard/sideboard/commander status.

Source decklists generally do not say which printing (set and card number) each card is from, so we need to use heuristics to figure that out.

We use a script to infer most likely set for each card based on some heuristics, and as far as I know, it always matches perfectly.

That just leaves situation where there are multiple printings of same card in same set.

If some of the printings are special (full art basics, Jumpstart basics, showcase frames etc.), these have been manually chosen to match every product.

If you see any errors for anything mentioned above, please report them, so they can be fixed.

That just leaves the case of multiple non-special printings of same card in same set - most commonly basic lands. In such case one of them is chosen arbitrarily, even though in reality a core set deck with 16 Forests would likely have 4 of each Forest in that core set, not 16 of one of them.

Feel free to create issue with data on exact priting if you want, but realistically we'll never get them all, and it's not something most people care about much.