Maigret Username OSINT — 3000+ Sites | $19/1K

Maigret Username OSINT — Find Accounts Across 3000+ Sites

Enter a username → discover every account registered under that handle across 3,000+ websites in minutes.

Built on Maigret, the leading open-source OSINT username checker. No API key, no cookies, no login required — Maigret checks public profile URLs directly.

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Use cases

• OSINT investigations — map a target's full digital footprint from a single username.
• Fraud & scam detection — verify whether a suspect handle appears on sites you'd expect (or wouldn't).
• Recruiting & background checks — find a candidate's GitHub, Dribbble, Behance, Stack Overflow, and 3000+ more.
• Brand & trademark monitoring — check whether your brand name is already registered on major platforms before launching.
• Personal digital audit — find all the accounts you've ever created and forgotten about.

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What it returns

One dataset item per found account:

{
  "username": "elonmusk",
  "site_name": "GitHub",
  "profile_url": "https://github.com/elonmusk",
  "site_url_main": "https://www.github.com/",
  "site_tags": ["coding"],
  "http_status": 200,
  "ids_usernames": {},
  "ids_links": [],
  "rank": 10,
  "query_time_ms": 312
}

Field	Description
username	The input username scanned
site_name	Platform name (e.g. "GitHub", "Twitter", "Reddit")
profile_url	Direct URL to the found profile
site_url_main	Platform homepage
site_tags	Category tags: social, coding, gaming, dating, video, music, etc.
http_status	HTTP response code from the profile URL
ids_usernames	Other usernames found on this site (cross-platform ID linking)
ids_links	External profile links extracted from the page
rank	Alexa-based site popularity rank (lower = more popular)
query_time_ms	Time taken to check this site

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Input

Parameter	Default	Description
usernames	—	Required. List of usernames to scan.
topSites	100	Check only the top N most-popular sites. 0 = all ~3000. Top 100 covers all major platforms.
tags	(all)	Restrict scan to sites with specific category tags (e.g. ["social", "coding"]).
timeoutPerSite	5	Seconds to wait per site before skipping.
maxConnections	50	Parallel connections (higher = faster, more aggressive).

Speed guide

Scope	Sites	Typical time
Top 50	~50	~20 seconds
Top 100 (default)	~100	~30–60 seconds
Top 500	~500	~3–5 minutes
All sites	~3000	~10–15 minutes

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vs. alternatives

	This actor	Manual Maigret CLI	Sherlock	Similar paid tools
Sites covered	3000+	3000+	~400	varies
API key needed	No	No	No	Often
Cloud-ready	Yes	No	No	Yes
Parallel usernames	Yes	One at a time	One at a time	Yes
Pay per result	Yes	N/A	N/A	Usually flat
Extracted IDs	Yes	Yes	No	Varies

The actor is a cloud wrapper around the same maigret engine the OSINT community uses — same coverage, zero setup friction.

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Example run (top 100 sites, username "elonmusk")

Found accounts include: GitHub, YouTube, Instagram, Reddit, Telegram, Twitter/X, WordPress, Flickr, SoundCloud, Spotify, and more — typically 15–30 results on a well-known username, 3–10 on an average person.

💰 Pricing & how we compare

Pay-per-result (PPE): $19 / 1K profiles found ($0.019 each). You are billed per account-found actually returned — plus the tiny apify-actor-start fee Apify waives for short runs. No subscription, no API key, no proxy fee on top.

Our edge: Maigret across 3000+ sites · parse_confidence per hit · clean downstream-ready JSON · no API key.

Pricing examples (pay only for what you get, minus Apify's 20%):

Volume	Cost
100 profiles	$1.90
1,000 profiles	$19.00
10,000 profiles	$190.00

How rivals price the same job (live Apify Store, checked 2026-06-09)

Actor	Their price	What they lack vs us
ntriqpro/maigret-actor	$0.02 / profile	5★ same Maigret core — we charm-undercut by 1¢ and add parse_confidence
apivault_labs/maigret-username-osint	$0.007 / profile	aggressive entry price, but newer / unrated

Prices above are competitors' live Store prices at the time of writing; ours is set to sit just below the strongest comparable while returning richer, quality-scored data.

🤖 Use with AI agents (MCP)

This actor is agent-ready (category MCP_SERVERS). Point any MCP client (Claude Desktop, Cursor, n8n AI, LangGraph) at it:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?actors=bovi/maigret-username-osint",
      "headers": { "Authorization": "Bearer <YOUR_APIFY_TOKEN>" }
    }
  }
}

More scrapers from our toolkit

Building a data pipeline? These actors pair well with this one — each runs on your own Apify account with the same pay-per-result pricing, no subscription:

• Patreon Scraper
• Pinterest Scraper
• Reddit Scraper
• Social Media Finder
• Telegram Channel Scraper
• Truth Social Scraper

Chain any of them together from the Integrations tab (the Run succeeded trigger) to build a multi-step workflow — one actor's output feeds the next.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.