X List Search Scraper

Discover public Lists on X (Twitter) that match the words you care about—curated collections people follow for news, hobbies, or industries. Each row is one List with its title, link, artwork, member facepile, and short context lines when the platform shows them.

Who it’s for

• Social & editorial teams scouting curated feeds around a theme.
• Researchers & analysts mapping how topics are organized into Lists.
• Partnerships & creators who want a structured snapshot instead of clicking through search by hand.

What you can do with it

• Run a keyword-style search and download matching Lists as rows.
• Cap how many rows you keep so runs stay predictable for cost and review.
• See what you searched on every row via searchQuery, next to a timestamp for the export.

How it works (in plain terms)

You type search words (for example a topic like “ai” or a niche phrase). The tool returns a set of List results and writes one dataset row per List, up to your maximum. You do not need to paste List URLs—only the words you want to explore.

Input

Field	Required	What it means
Search words (query)	Yes	What to look for among public Lists.
Maximum results (maxResults)	No	Upper limit on how many List rows to save (default 100).

Output

• One row per List (until your cap), in the order returned for your search.
• Identity & link: object_id, human-readable title topic, and url (path-style link to the List).
• Visuals: primary_image.original_info — banner URL, height / width, and optional focus_rect for cropping hints.
• Description line: supporting_text when the List has a short blurb.
• People preview: facepile_urls — usually several objects with profile_image_url_https for member avatars.
• Context chips: result_contexts — one or more blocks; each has result_context.display_string (e.g. follower line, member count) and types (such as followers_context or members_context).
• Export metadata: searchQuery repeats your search words; scrapedAt is when that row was saved.

Some Lists may omit supporting_text, primary_image, or parts of result_contexts.

Sample output (one dataset row)

{
  "object_id": "1705702737835643273",
  "topic": "AI Education",
  "url": "twitter.com/i/lists/1705702737835643273",
  "primary_image": {
    "original_info": {
      "url": "https://pbs.twimg.com/list_banner_img/1706562024615071744/NvN7KLRj?format=jpg&name=orig",
      "height": 813,
      "width": 2441,
      "focus_rect": {
        "h": 1,
        "w": 1,
        "x": 200,
        "y": 200
      }
    }
  },
  "supporting_text": "AI Companies that help educators or students.",
  "facepile_urls": [
    {
      "profile_image_url_https": "https://pbs.twimg.com/profile_images/1492616506/Brian-Med-Green-Fin_mini.png"
    },
    {
      "profile_image_url_https": "https://pbs.twimg.com/profile_images/1365726769752416256/bxJjHjEK_mini.jpg"
    },
    {
      "profile_image_url_https": "https://pbs.twimg.com/profile_images/1548209223065997313/XBecCCv7_mini.jpg"
    }
  ],
  "result_contexts": [
    {
      "result_context": {
        "display_string": "8.8K followers including @BrianRoemmele",
        "types": [
          {
            "type": "followers_context"
          }
        ]
      }
    },
    {
      "result_context": {
        "display_string": "194 members",
        "types": [
          {
            "type": "members_context"
          }
        ]
      }
    }
  ],
  "searchQuery": "ai",
  "scrapedAt": "2026-03-25T08:51:41.223Z"
}

Good to know

• Results depend on what X surfaces for your words; try different phrasing if you see few rows.
• Respect X’s rules and applicable laws when using exported data.