X (Twitter) Keyword Monitor — New Mention Alerts (Vigia)

Monitor X/Twitter for a brand, product or keyword and get only NEW posts since last check, with a mention-velocity spike signal. Charged only on new mentions, never per run. Ideal for social-listening and reputation agents.

Free tier — 10 results free on every run

The first 10 results of every run are free, on every run you ever make — not a one-off trial. Run it on your own subjects and see the real output before you are billed for a single result.

One guard: the free allowance never covers more than half of a run, so a run returning 6 results gets 3 free. That keeps the offer sustainable.

What it does

Watch X/Twitter for a brand or keyword and get only new posts, with a mention spike alert. You get only what changed since your last check — never a full re-dump to diff yourself.

Why Vigia — 5 advantages a raw scraper can't match

1. You pay the alert price only for real change. New-mention alerts are billed only for genuinely new mentions since your last check. A quiet run bills just the small source-check fee (the cost of looking) — never the alert price on unchanged data. Raw scrapers bill every row of a full re-scan every run.
2. Never billed on a failed source. The source check is charged only when the source actually responded. If it's down, you don't pay for our outage.
3. Append-only delta + spike signal. The first monitored run stores a free baseline; later runs deliver only what's new, plus a velocity-spike alert when volume suddenly surges (trend / review-bomb / hiring-surge).
4. Hard cost cap you control. Set maxTotalChargeUsd and the run can never bill above it — predictable spend, no surprise invoice.
5. Agent-ready output. Clean, normalized rows and a RUN_SUMMARY.json with ready-to-use signals — chainable from any MCP / A2A agent in one step.

Example input

{
  "keywords": [
    "your brand",
    "competitor name"
  ],
  "monitorEnabled": true,
  "maxTotalChargeUsd": 1.0
}

Set monitorEnabled: true so the first run stores a free baseline and later runs return only new results. Pin a monitorId to keep separate targets from sharing state.

Output

Each row is a normalized change record: record_id, query_id, title, url, author, published_at, score, text. A RUN_SUMMARY.json accompanies every run with the aggregated signal (counts, velocity spikes, trend).

How you're charged

• Mention alert — billed once per new mention since the last check (this is the only charge that scales with change).
• Source check ($0.05) — billed once per monitored target per run, only when the source responded. A failed source is free.
• A quiet run bills only the source check ($0.05), never the alert price. Vigia never scrapes the source itself; it chains a licensed scraper, caps every call, and passes you only the delta.

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Part of the Vigia monitoring suite — change-only billing, outage-safe, agent-ready.

Related tools

• Already know the account? Watch it directly instead of searching. → X (Twitter) Profile Scraper

How to use it in 3 steps

1. Click Try for free and fill in Search keywords (keywords).
2. Optional: adjust the other fields; every one has a description and a sensible default.
3. Click Start and download the results as JSON, CSV or Excel, or read them from the API.

Use cases

• Brand research
• Trend analysis
• Lead discovery

Use it from code (API)

Every Apify Actor is an API. Start a run and read the results with one call.

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("om_kh/twitter-x-search-scraper").call(run_input={"keywords": ["your brand", "competitor name"]})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('om_kh/twitter-x-search-scraper').call({
    "keywords": [
        "your brand",
        "competitor name"
    ]
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

One HTTP call (cURL) — runs the Actor and returns the dataset in the same response:

curl -X POST "https://api.apify.com/v2/acts/om_kh~twitter-x-search-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"keywords": ["your brand", "competitor name"]}'

Integrations: n8n, Make, Zapier, Google Sheets

• n8n — the official Apify node, operation Run Actor and get dataset, Actor om_kh/twitter-x-search-scraper.
• Make — Apify › Run an Actor, then Apify › Get Dataset Items.
• Zapier — Apify › Run Actor; map the dataset items into your next step.
• Google Sheets, webhooks, Slack — add an integration from the Integrations tab of this Actor.
• Schedules — run it every hour or day from Schedules in Apify Console.

Use it from an AI agent (MCP)

This Actor runs in Standby and speaks the Model Context Protocol at /mcp, exposing one tool, x_search_new_posts. Add it to Claude Desktop, Cursor, VS Code or any MCP client through the Apify MCP server (https://mcp.apify.com), or call the Actor's Standby URL directly with the same JSON as the run input.

FAQ

Is it legal to scrape X (Twitter)? This Actor collects only publicly available X (Twitter) data and never logs in. You are responsible for how you use it; check X (Twitter)'s terms and your local law (GDPR, CCPA) if you store personal data, and ask a lawyer if unsure.

Do I need an account, cookies or an API key? No. You only need an Apify account to run it.

What data do I get? Matching posts with text, likes, reposts, replies and author. Download it as JSON, CSV, Excel, HTML or XML, or read it from the API.

Am I charged when something fails? No. An input that fails is listed with its reason in the run summary and is never charged.

Can I run it on a schedule? Yes. Create a schedule in Apify Console (hourly, daily, weekly) and connect webhooks, Google Sheets, Slack, n8n, Make or Zapier.

Can I use it from Python, JavaScript or an AI agent? Yes: see the code samples above, or connect AI agents through MCP with the x_search_new_posts tool.

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