Martindale-Hubbell Attorney Scraper — AV Preeminent Ratings

One row per attorney from Martindale-Hubbell, with fullName, jobTitle, firmName, practiceAreas, street/city/state/postalCode, phone and website where published, yearOfFirstAdmission, barAdmissions (every bar and court), lawSchool, university, isln — and the credential Martindale has been publishing since 1868: the AV Preeminent® Peer Review Rating, as peerRatingTier, peerRating, peerReviewCount and the five sub-scores in peerReviewBreakdown. Filter by country, state/province, city, practice area, rating tier and years since admission — or paste attorney profile URLs and scrape those directly. No login. No cookies. No CAPTCHA solving.

Martindale is the credential file, not the contact file. It returns the AV peer ballot broken out into its five named sub-scores, plus the ISLN and the full bar-admission list — the credential side of Martindale rather than a single rating label. Phone is 1.8% here, so read Honest limits before you buy.

Scope

Measured on Martindale's live sitemap index on 2026-08-12: 94 attorney sitemap chunks — 76 across 52 US regions, 13 Canadian provinces and territories, 5 US territories, at up to 50,000 attorney URLs per chunk. Texas alone publishes 142,408 attorney URLs; Yukon publishes 107. Those are counts read off the files, not quoted from a marketing page.

🚀 Quick start

The Actor ships prefilled with a working demo. Click Try for free, press Start, change nothing.

{
  "country": "usa",
  "states": ["texas"],
  "maxItems": 50,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Measured on that exact input over three runs, 2026-08-12: 50 Texas attorneys in 35–50 seconds, 52–53 requests, 96–100% clean on the first attempt, 0 duplicates, costing $0.15. Every field in the sample row below came out of a run like that one.

The wedge: the AV Preeminent peer rating

Martindale-Hubbell has been rating lawyers since 1868. Its rating is not a star average from clients — it is a confidential ballot of other attorneys and judges, scored on Legal Knowledge, Analytical Capability, Judgment, Communication and Legal Experience, and it comes in three tiers:

Tier	What it means
AV Preeminent®	The top tier. A large number of the lawyer's peers rank them at the highest level of professional excellence.
Distinguished	An excellent rating for a lawyer with some experience; widely respected by peers.
Notable	Recognised by a large number of peers for strong ethical standards.

This field is not on Avvo, not on Justia, and not on any state bar registry. It is the oldest and most-cited attorney credential in the United States, and it is what a legal-tech, legal- recruiting, expert-witness, litigation-finance or law-firm-M&A buyer actually wants to sort on. Every row carries the tier, the numeric peer score and the peer review count; peer-reviewed attorneys also carry the five sub-scores broken out.

Measured on 490 unique Texas attorneys: 25.5% carry a peer rating. Of 490 rows, 77 AV Preeminent, 34 Distinguished, 8 Notable.

Read this before you buy rows

1. The sitemaps slice by STATE ONLY. Martindale's browse and listing pages are behind a Cloudflare interactive challenge, so city, practice-area and rating filters are applied after a profile has been fetched. That is cheap for a state pull and expensive for a narrow one — measured, Texas unfiltered returned 250 attorneys from 250 fetches (1.0 fetches per row), while Texas + cities: ["Austin"] + avPreeminentOnly returned 12 attorneys from 657 fetches (55 fetches per row). You are billed per attorney returned, so that costs you time and this Actor its proxy budget — not your money.
2. Most Martindale records were never claimed by the attorney. Credential fields are near-universal (ISLN 100%, bar admissions 99.6%); contact fields are not (phone 1.8%, website 5.1%). The fill table below is the whole story and it is not flattering in one column on purpose.
3. There is no email address in this dataset, anywhere. Martindale publishes none, for any attorney. See the FAQ.
4. Law firms are a different record. /organization/… URLs are rejected with an error rather than silently producing a half-empty attorney row.
5. A missing rating is a fact about Martindale, not a scraping failure. peerReviewCount: 0 means "rated by nobody"; null means Martindale did not render that rating for this attorney.

What you get — one row per attorney

Group	Fields
Identity	profileUrl, profileId, isln, fullName, photoUrl, scrapedAt
Work	jobTitle, firmName, firmProfileUrl, practiceAreas
Address	street, city, state, postalCode, country, addressFull, latitude, longitude, officeCount, offices[]
Contact	phone, phones[], fax, website, websites[]
Peer rating	peerRatingTier, isAvPreeminent, peerRating, peerReviewCount, peerReviewBreakdown{5}, awards[]
Client / other ratings	clientRecommendPercent, clientReviewCount, avvoRating, avvoReviewCount, overallRating, overallReviewCount
Credentials	yearOfFirstAdmission, yearsSinceAdmission, barAdmissions[], lawSchool, lawSchoolDegree, lawSchoolYear, university, universityDegree, universityYear

Conventions, stated once: scrapedAt is ISO-8601 UTC. peerRating, avvoRating and overallRating are on a 0–5 scale; clientRecommendPercent is a percentage (0–100). yearsSinceAdmission is computed from yearOfFirstAdmission against the current UTC year. The dataset ships four table views — Attorneys, Peer ratings, Contact details and Credentials — so you can look at the slice you bought without writing a transformation. The run also writes NEXT_SKIP_FIRST to the key-value store.

Field fill — measured on 490 unique Texas attorneys

Sorted by fill, highest first. Martindale's sitemaps list every attorney it has a record for, and most of those records were never claimed.

Field	Fill
fullName, city, state, addressFull, isln, profileUrl	100%	every row
barAdmissions	99.6%	the bars and courts, split into a list
yearOfFirstAdmission / yearsSinceAdmission	98.2%
postalCode	96.7%
street	91.0%	the rest publish a city-only address
lawSchool	80.0%	lawSchoolDegree and lawSchoolYear alongside
practiceAreas	79.2%	4.7 areas per attorney on average
university	58.0%	undergraduate
jobTitle	52.0%	Partner, Member, Associate, Of Counsel, judges' titles
firmName / firmProfileUrl	36.9%	many listings are solo or unaffiliated
peerRating (numeric)	25.5%	the AV field — the reason this Actor exists
peerRatingTier	24.3%	AV Preeminent / Distinguished / Notable
awards	24.3%	includes Client Champion tiers
peerReviewBreakdown	9.0%	the five sub-scores, when peer reviews exist
website	5.1%	claimed profiles only
overallRating	4.3%	blended peer + client
clientRecommendPercent / clientReviewCount	3.7%
phone	1.8%	claimed, subscribing profiles only
latitude / longitude	1.8%
photoUrl	1.4%
avvoRating	0.4%	only on profiles linked across Martindale and Avvo

The headline that could mislead you: this is not a phone-number product. Martindale publishes a phone on roughly 1 profile in 50 on a random state walk, and no email address for any attorney, ever.

Fill varies by state and by slice — a walk through a state's older, more established attorneys returns more ratings than one through recent admissions. Every run prints its own measured fill in the log.

How to run it

A. A plain state pull (the cheapest mode)

Every profile fetched is a row emitted: 1.0 fetches per row, no waste.

{ "country": "usa", "states": ["new-york", "new-jersey"], "maxItems": 2000 }

B. The AV Preeminent slice

The filter runs after the fetch, so budget roughly 6 fetches per row (15.7% of 490 Texas attorneys qualified). The log prints the running match rate every 200 fetches.

{
  "country": "usa",
  "states": ["texas"],
  "avPreeminentOnly": true,
  "minYearsSinceAdmission": 25,
  "maxItems": 500
}

C. A practice-area cut

practiceAreas is a dropdown of Martindale's root area names, matched as a case-insensitive substring — so Criminal also keeps "Criminal Defense" and "Criminal Law". Martindale's taxonomy is long-tail (50 Wyoming attorneys produced 202 distinct area strings), so anything the dropdown does not list goes in practiceAreaKeywords as free text. The two are OR-ed together.

{
  "country": "usa",
  "states": ["florida"],
  "practiceAreas": ["Personal Injury", "Medical Malpractice"],
  "practiceAreaKeywords": ["Insurance Coverage"],
  "maxItems": 300
}

D. Known profiles — paste the URLs

Sitemap enumeration is skipped entirely. Only /attorney/… URLs are accepted; Martindale's directory pages are Cloudflare-walled and /organization/… firm pages are a different record.

{
  "profileUrls": [
    "https://www.martindale.com/attorney/mr-william-mather-mckellar-1808340/"
  ]
}

E. Resuming a big state across runs

Run 1 stops and logs Resume: set skipFirst to N, and writes the same number to the key-value store as NEXT_SKIP_FIRST. Feed it to run 2 and schedule the pair on Apify Schedules if you want it standing.

{ "country": "usa", "states": ["texas"], "skipFirst": 1000, "maxItems": 1000 }

Measured: two contiguous 120-attorney slices joined this way shared 0 rows — 240 rows, 240 distinct profile ids.

Sample row

One real row, from a real run:

{
  "profileUrl": "https://www.martindale.com/attorney/mr-william-mather-mckellar-1808340/",
  "profileId": "1808340",
  "isln": "904947272",

  "fullName": "William Mather McKellar",
  "jobTitle": "Member",
  "firmName": "McKellar, Tiedeken & Scoggin LLC",
  "firmProfileUrl": "https://www.martindale.com/organization/mckellar-tiedeken-scoggin-llc-1445765/…",
  "practiceAreas": ["Insurance Defense Law", "Insurance Coverage Law", "Personal Injury Litigation",
                    "Products Liability Litigation", "Environmental Litigation", "Toxic Tort Litigation"],

  "street": "702 Randall Ave.",
  "city": "Cheyenne",
  "state": "WY",
  "postalCode": "82003-0748",
  "country": "US",
  "addressFull": "702 Randall Ave., Cheyenne, WY 82003-0748",
  "latitude": null,
  "longitude": null,

  "phone": null,
  "phones": [],
  "fax": null,
  "website": null,
  "websites": [],

  "peerRatingTier": "AV Preeminent",
  "isAvPreeminent": true,
  "peerRating": 4.9,
  "peerReviewCount": 3,
  "clientRecommendPercent": null,
  "clientReviewCount": null,
  "avvoRating": null,
  "avvoReviewCount": null,
  "overallRating": null,
  "overallReviewCount": 0,
  "awards": ["AV Preeminent"],
  "peerReviewBreakdown": {
    "legalKnowledge": 4.9, "analyticalCapability": 4.9, "judgment": 4.9,
    "communication": 4.9, "legalExperience": 4.9
  },

  "yearOfFirstAdmission": 1982,
  "yearsSinceAdmission": 44,
  "barAdmissions": ["1982, Wyoming", "1982, Colorado",
                    "1982, U.S. District Court, District of Wyoming, U.S. Court of Appeals, Tenth Circuit and U.S. Supreme Court"],
  "lawSchool": "University of Wyoming",
  "lawSchoolDegree": "J.D.",
  "lawSchoolYear": 1982,
  "university": "University of Northern Colorado",
  "universityDegree": "B.A.",
  "universityYear": 1979,

  "photoUrl": null,
  "officeCount": 1,
  "offices": [{ "label": "Cheyenne, WY", "street": "702 Randall Ave.", "city": "Cheyenne",
                "state": "WY", "postalCode": "82003-0748", "phone": null, "fax": null }],
  "scrapedAt": "2026-08-12T22:35:19.477Z"
}

Three fields people misread, so they are named to prevent it:

• clientRecommendPercent is a percentage, not a star rating. Martindale renders the client tile as "100%" — the share of reviewing clients who recommend the attorney — while peerRating, avvoRating and overallRating are on a 0–5 scale. Mixing them would put a 100 in a 5-point column.
• peerReviewCount: 0 means "rated by nobody"; peerReviewCount: null means "Martindale did not render that rating for this attorney". They are different facts and are kept different.
• peerRating is a peer ballot, clientRecommendPercent is client feedback. An attorney can have one, both or neither.

Input

Grouped in the Console as Step 1 | Choose the market · Step 1 | Or paste profile URLs · Step 2 | Filter the rows · Step 3 | Choose how deep to go · Step 4 | Set limits and resume · Connection settings. Nothing is required; everything that matters is prefilled.

Field	Type	Default	What it does
country	select	usa	usa (76 sitemap chunks, 52 regions), canada (13) or territories (5).
states	multi-select	["texas"]	State/province picked from a dropdown of all 70 regions Martindale publishes. Empty walks the whole country alphabetically. The only pre-fetch filter.
profileUrls	list	—	Paste /attorney/… URLs to skip enumeration. Directory URLs are walled and firm URLs are rejected.
cities	list	—	Keep only these office cities. Exact, case-insensitive. Applied after fetching.
practiceAreas	multi-select	—	61 root area names, matched as case-insensitive substring. Applied after fetching.
practiceAreaKeywords	list	—	Free-text escape hatch for the long tail; OR-ed with the dropdown.
avPreeminentOnly	bool	false	Keep only AV Preeminent attorneys. ~6 fetches per row.
ratedOnly	bool	false	Keep any peer or client rating. ~4 fetches per row.
withPhoneOnly	bool	false	Keep only attorneys with a published phone. ~50 fetches per row — read the fill table first.
withWebsiteOnly	bool	false	Keep only attorneys with a firm website. ~20 fetches per row.
minYearsSinceAdmission	int	0	Admitted at least this many years ago. 98.2% fill, so this filter is cheap.
includePeerBreakdown	bool	true	Include the five peer sub-scores. No extra request.
includeOffices	bool	true	Include the full office array. The primary office is always flattened into the top-level address fields.
maxItems	int	50	Cap on attorneys returned. Also your budget control.
skipFirst	int	0	Resume where the previous run stopped.
maxConcurrency	int	4	Workers in flight (1–8). The 600 ms pacer sets the real rate.
proxyConfiguration	proxy	Apify RESIDENTIAL	Leave it. See the transport ladder.

Pricing

$0.003 per attorney returned — $3 per 1,000 — charged on the attorney-scraped event. No monthly platform fee from this Actor.

Run	Attorneys	Cost
The prefilled demo, no edits	50	$0.15
A city sample	250	$0.75
A practice-area list	1,000	$3.00
A serious Texas pass	5,000	$15.00
Every attorney Texas publishes	142,408	$427.22

You are charged for rows delivered, never for a profile that was fetched and then filtered out, and never twice for the same attorney — duplicate profile ids are dropped at enumeration, before anything is fetched. Rows are charged as they are pushed, so if you hit a budget cap you get whole rows and stop, not a half-billed dataset. maxItems is your hard cost cap.

Honest limits

• No email addresses. Martindale publishes none, for any attorney. Anyone selling you "Martindale emails" generated them somewhere else.
• Phone is 1.8% and website is 5.1% on a random state walk of 490 Texas attorneys. Those fields live only on claimed, subscribing profiles. This is a credentials-and-ratings product, not a dialler list. If you need contactable rows, pair it with justia-lawyer-scraper (claimed-profile subset, phone near-universal) or a state bar registry, and use this Actor for the credential and rating fields.
• City and practice-area filtering happens after the fetch, because Martindale's city listings are Cloudflare-walled. Narrow asks are slow — 55 fetches per row on the Austin + AV Preeminent measurement. There is no workaround that does not involve attacking the challenge, which this Actor does not do. The cheap way to slice a city: pull the state unfiltered into a dataset (1.0 fetches per row) and filter it yourself — you get every other city for free.
• Law firms are a different record. /organization/… URLs are rejected rather than silently producing a half-empty attorney row.
• Ratings are Martindale's, not ours. A missing rating means Martindale never published one; it is not a scraping failure. Peer reviews submitted before 2008 are not displayed by Martindale, so some long-standing attorneys show a tier with no visible reviews behind it — which is why peerRatingTier is 24.3% while peerReviewBreakdown is 9.0%.
• avvoRating is sparse (0.4%) — Martindale and Avvo are sister sites and the tile only appears on profiles that are linked across both.
• Canada and the territories are much smaller files. Yukon publishes 107 profile URLs. Expect fewer ratings and far fewer claimed profiles outside the US.
• Nationwide and multi-state runs deduplicate within a run. Across runs, use skipFirst.

How it works (technical)

1. Read https://www.martindale.com/sitemap_profiles.xml, the index Martindale's own robots.txt publishes. /search/, /assets/html/profiles/ and /marketyourfirm/… are Disallowed and this Actor never touches them.
2. Pick the atty_<country>_<region>_NNNN_profiles.xml chunks for your country and states (up to 50,000 attorney URLs each) and stream the <loc> values out.
3. Deduplicate on the numeric profile id before anything is fetched, then skip skipFirst.
4. Fetch each /attorney/{name}-{id}/ page over plain HTTP through one pinned Apify RESIDENTIAL session, paced at 600 ms.
5. Merge two sources on the page: the JSON-LD LegalService block (name, firm, address, geo, phones, website, photo, awards, alumni) plus the rendered HTML for what Martindale keeps out of JSON-LD — the peer score and its five sub-scores, the client score, "Year of First Admission", the bar-admission list, the ISLN, the university and the full office list. Ratings are always read from the labelled blocks, because the JSON-LD aggregateRating collapses peer and client into one number without saying which.
6. Apply your filters, push in batches, charge on push.

Why the sitemaps and not the listing pages. Measured 2026-08-12 through a working Apify RESIDENTIAL session — the same session that was fetching profile pages at 100% seconds earlier:

Page	Result
/all-lawyers/austin/texas/	HTTP 403, "Just a moment…", 0 attorney links
/all-lawyers/austin/texas/?page=2	HTTP 403
/by-location/austin-lawyers/texas/	HTTP 403
/by-location/texas-lawyers/	HTTP 403
/family-law-lawyer/texas/austin/	HTTP 403
/attorney/{name}-{id}/	HTTP 200, full profile
sitemap_profiles.xml and the per-state chunks	HTTP 200

The transport ladder. Everything below was measured through Apify Proxy, not from a laptop. A home broadband line reaches martindale.com without a proxy; an Apify container does not, so the home result is reported and then ignored.

Rung	Result
Direct, no proxy, residential home line	200 — but not a shippable rung, no Apify container has a residential IP
Apify datacenter, new exit IP every request	0/5 — HTTP 403 + Cloudflare challenge
Apify datacenter, pinned session	100/130 requests clean on the first attempt = 76.9%
Apify RESIDENTIAL, new exit IP every request	24/25 = 96.0%
Apify RESIDENTIAL, pinned session, 250 ms pacing	143/161 = 88.8% first attempt
Apify RESIDENTIAL, pinned session, 600 ms pacing	122/122 = 100%, then 247/257 = 96.1% over a 250-attorney run, 0 failures

Two findings worth keeping:

1. Pinning matters more than the pool. A residential exit Cloudflare has already let through keeps being let through; a fresh IP on every request pays the challenge lottery each time.
2. Pacing beat concurrency. At 250 ms the failures were HTTP 429, not challenges — Martindale rate-limits the exit IP, and a pinned session cannot rotate away from it for free. Backing off to 600 ms removed them and made the run faster end to end (79 s vs 86 s for 120 attorneys), because every retry costs a request plus its backoff. The Actor is therefore paced, not parallelised; maxConcurrency only controls how many workers wait on the pacer.

Anything still challenged or rate-limited burns its proxy session and retries on a fresh one. Across every validation run, 0 attorneys were lost to the transport.

Uniqueness — measured, not asserted

• Texas publishes 142,408 attorney URLs across 3 contiguous sitemap chunks: 0.00% duplicate profile ids across all three.
• Every validation run reported 0.00% duplicates in its own output, including the 50-row prefilled demo (50 rows, 50 distinct profile ids).
• Two contiguous slices joined with skipFirst (120 + 120 attorneys) shared 0 rows: 240 rows, 240 distinct profile ids.

Profile ids are deduplicated at enumeration, before anything is fetched, and re-asserted on the way out — so a duplicate can reach neither your dataset nor your bill. Every run ends with a Resume: set skipFirst to N line and writes the same number to the key-value store as NEXT_SKIP_FIRST.

When a run fails

This Actor fails loudly rather than handing you a green run with an empty dataset.

• 0 rows throws, with the fetch count, how many were blocked, dead, unparseable and how many your filters removed — plus which of those is the likely cause.
• A state or country slug that does not exist throws, listing the slugs Martindale actually publishes right now.
• A sitemap index with no attorney sitemaps throws rather than reporting a successful empty run.
• More than 20% of HTTP-200 profile pages failing to parse throws — that is a template change, and shipping degraded rows would be worse than stopping.
• skipFirst past the end of the enumerated list throws instead of returning nothing.
• A firm /organization/… URL throws instead of emitting a half-empty attorney row.
• Running out of candidates before maxItems is a warning, not a failure — the rows you got are real, there just were not more that matched.

Who buys this

You are…	You use it to…
Legal-tech / practice-management SaaS (Clio, MyCase, Filevine)	Build an ICP list from firmName + officeCount + practiceAreas, and prioritise the AV Preeminent partners who set software budgets.
Legal recruiters and lateral-hire desks	Rank candidates on a peer credential rather than a self-written bio: peerRatingTier + yearsSinceAdmission + lawSchool + barAdmissions.
Expert-witness and litigation-support brokers	Find AV-rated specialists by practiceAreas in the venue's state, with barAdmissions proving they can appear there.
Litigation funders and law-firm M&A advisors	Screen firms by how many AV Preeminent attorneys they carry, and who is 25+ years in (minYearsSinceAdmission) and near succession.
Legal-directory and rating aggregators	Join on isln, the stable Martindale identifier present on 100% of rows, and carry the five peer sub-scores broken out rather than a single rating label.
Bar associations and CLE providers	Segment by yearOfFirstAdmission cohort and barAdmissions jurisdiction.

How this differs from the sibling legal Actors

Actor	What it is	Why you would use it instead
This Actor	Martindale-Hubbell, 94 attorney sitemap chunks across 70 regions	You want the AV Preeminent peer rating with its five sub-scores, the ISLN, the full bar-admission list and law school — the credential fields.
avvo-scraper	Avvo	You want the client-review side and the Avvo 10-point score.
ca-attorney-scraper	The California State Bar's own file	You want every licensed attorney in California, with licence status and discipline history, from the official record.
justia-lawyer-scraper	The Justia directory, claimed-profile subset	You want contactable leads — phone and website are near-universal there because it only covers claimed profiles.
state-bar-attorney-scraper	A state's own registration file	You want registration status, admission date and discipline history for a whole state.
superlawyers-attorney-scraper	Super Lawyers selections	You want the peer-nominated annual list rather than a standing rating.

The honest summary: Justia is where you go for phone numbers, Martindale is where you go for the peer rating. The usual play is to pull the AV Preeminent slice here and enrich the contact details elsewhere.

FAQ

Can I get attorney emails? No — and nobody honestly can, from this source. Martindale publishes no email address for any attorney, so there is no email field and nothing in this Actor can invent one. What you do get is phone (1.8%), website (5.1%) and firmProfileUrl (36.9%), plus the credential fields at 98–100%. If email is the point of your project, start from a source that publishes contact data and use this Actor for the rating.

Does this need an account or login? No. It reads public directory pages listed in Martindale's own robots.txt sitemaps. No login, no cookies, no CAPTCHA solving.

Can I get every attorney in a state? Yes. Set the state, leave the filters off, set maxItems. Texas is 142,408 attorney URLs, so a full pull is a multi-run job — use the Resume: set skipFirst to N line the run prints.

Can I filter to one city? Yes, but the filter runs after each profile is fetched, because Martindale's city listings are walled. A big city inside its own state costs a handful of fetches per row; a small town can cost hundreds, and Austin + AV Preeminent measured 55 fetches per row. Cheaper: pull the state and filter the dataset yourself.

How do I get only AV Preeminent lawyers? Set avPreeminentOnly: true. Measured on 490 Texas attorneys, 77 qualified (15.7%), so raise maxItems and give the run time; the log prints the running match rate.

Do I get charged for rows that get filtered out? No. You are charged per attorney returned, on push. A narrow filter costs time and proxy budget, not money.

Two runs, will I get duplicates? Not if you use skipFirst with the number the previous run logged. Measured: two contiguous 120-row slices shared 0 rows out of 240.

Does it need a proxy? Yes — Apify Proxy with the RESIDENTIAL group, which is the default. A datacenter IP that rotates on every request measured 0/5; a pinned datacenter session 76.9%; a pinned residential session at 600 ms 100% then 96.1%.

Why do so many rows have no firm? Because 36.9% is the real number. Martindale lists solo practitioners, judges, in-house counsel and unaffiliated attorneys with no firm record attached.

What is ISLN? Martindale's own International Standard Lawyer Number — a stable per-attorney identifier, present on 100% of rows. It is the right key for de-duplicating against another Martindale pull.

Does it work outside the US? Canada (13 provinces and territories) and the US territories (5), yes — set country. The files are much smaller and much sparser; Yukon publishes 107 profile URLs.

Will a run ever succeed with zero rows? No. A run that emits nothing throws, and the error says how many pages were fetched, how many were blocked or dead, and how many your filters removed.

Something looks wrong — how do I debug it? Read the run log. Every run prints its own field fill, its own duplicate rate, and the transport statuses it saw, so you can compare your slice against the numbers on this page instead of guessing.

Can I schedule it? Yes — Apify Schedules. Pair it with skipFirst / NEXT_SKIP_FIRST to walk a large state a slice at a time.

⚠️ Legal & fair use

This Actor reads public directory pages that Martindale-Hubbell publishes and lists in its own robots.txt sitemaps, and it does not touch the Disallowed paths (/search/, /assets/html/profiles/, /marketyourfirm/…). It does not log in, and it collects no data behind any authentication or CAPTCHA.

Rows describe named individuals, so they are personal data. You are responsible for complying with Martindale's terms and with how you use the data. Attorney advertising, solicitation and anti-spam rules may apply to your outreach — including GDPR, CCPA, CAN-SPAM and state bar rules on soliciting lawyers and their clients.

Martindale-Hubbell®, AV®, AV Preeminent® and Martindale® are trademarks of their owner; this Actor is not affiliated with, endorsed by or sponsored by them.

Feedback

Found a missing field or want a new filter? Open an issue on the Issues tab.

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