mcpbeat

Twitter Mention Tracker

gooseworks-ai/twitter-mention-tracker

> Search and scrape Twitter/X posts using Apify. Use when you need to find tweets, track brand mentions, monitor competitors on Twitter, or analyze Twitter discussions.

3k tokens
context cost
the whole folder, loaded on every use
3
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
1086
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/gooseworks-ai/goose-skills --skill twitter-mention-tracker

What comes with it

8 402 bytes besides the instruction
scripts/search_twitter.py
skill.meta.json

The instruction itself

10 sections, as written by the author

Twitter Mention Tracker

Search Twitter/X posts using the Apify apidojo/tweet-scraper actor.

Quick Start

Requires APIFY_API_TOKEN env var (or --token flag).

# Search with date range (recommended -- uses Twitter native since:/until: operators)
python3 skills/twitter-mention-tracker/scripts/search_twitter.py \
  --query "YourCompany" --since 2026-02-15 --until 2026-02-23

# Quick summary of recent mentions
python3 skills/twitter-mention-tracker/scripts/search_twitter.py \
  --query "@yourhandle" --max-tweets 20 --output summary

# Search without date filtering
python3 skills/twitter-mention-tracker/scripts/search_twitter.py \
  --query "AI content marketing" --max-tweets 50

Date Filtering

Important: The apidojo/tweet-scraper actor's built-in date parameters are unreliable.

This script embeds since:YYYY-MM-DD and until:YYYY-MM-DD directly into the search query

string, using Twitter's native advanced search syntax. This ensures date filtering works

correctly server-side.

How the Script Works

  • Builds a search term with the query quoted and date operators appended
  • Calls the Apify apidojo/tweet-scraper actor via REST API
  • Polls until the run completes, then fetches the dataset
  • Deduplicates by tweet ID/URL
  • Applies optional keyword filtering (client-side)
  • Sorts by likes (descending) and outputs JSON or summary

CLI Reference

| Flag | Default | Description |

|------|---------|-------------|

| --query | *required* | Search query (quoted in Twitter search) |

| --since | none | Start date YYYY-MM-DD (inclusive) |

| --until | none | End date YYYY-MM-DD (exclusive) |

| --max-tweets | 50 | Max tweets to scrape |

| --keywords | none | Additional filter keywords (comma-separated, OR logic) |

| --output | json | Output format: json or summary |

| --token | env var | Apify token (prefer APIFY_API_TOKEN env var) |

| --timeout | 300 | Max seconds to wait for the Apify run |

Direct API Usage

{
  "searchTerms": ["\"YourCompany\" since:2026-02-15 until:2026-02-22"],
  "maxTweets": 50,
  "searchMode": "live"
}

Output Format

Tweets are returned as JSON array sorted by likes. Each tweet has:

{
  "id": "...",
  "text": "Tweet text...",
  "fullText": "Full tweet text...",
  "likeCount": 42,
  "retweetCount": 5,
  "replyCount": 3,
  "viewCount": 1200,
  "createdAt": "2026-02-18T12:00:00.000Z",
  "author": {"userName": "handle", "name": "Display Name", ...},
  "twitterUrl": "https://twitter.com/..."
}

Common Workflows

Competitor Monitoring

python3 skills/twitter-mention-tracker/scripts/search_twitter.py \
  --query "CompetitorName" --since 2026-02-15 --until 2026-02-23 --output summary

Brand Mention Tracking

python3 skills/twitter-mention-tracker/scripts/search_twitter.py \
  --query "@YourHandle OR \"YourBrand\"" --max-tweets 100

How to use it

Copy the folder

Take gooseworks-ai/twitter-mention-tracker from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.