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mcp-servers-snowleo

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MCP servers exposing Snow Leo Data web-data tools on Apify

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Last scanned: 9/18/2026
Install in Claude Code / Claude Desktop
Method: Manual
Claude Code CLI
git clone https://github.com/MagzhanSan/mcp-servers-snowleo
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
💡 Clone https://github.com/MagzhanSan/mcp-servers-snowleo and follow its README for install instructions.
Casos de uso

Resumen de MCP Servers

# Snow Leo Data — MCP servers

Five remote MCP servers that give an AI agent **21 web-data tools**: local business
leads, job listings, marketplace catalogues, compliance records and public media
feeds. Every tool is a published Apify Actor, exposed over the Model Context
Protocol by Apify's own hosted gateway at `mcp.apify.com`.

- **Transport:** Streamable HTTP. No install, no npm package, no local process.
- **Auth:** OAuth with your own Apify account (or a Bearer token).
- **Billing:** you pay Apify directly, per result. Prices are listed below.

The servers are split by subject on purpose. An agent handed twenty-one tools at
once picks badly; an agent handed four tools that all answer one kind of question
picks well. Connect only the server you need.

---

## The five servers

| Server | Tools | What it answers | URL |
|---|---|---|---|
| **Leads & Contacts** | 5 | "Who are the businesses here, and how do I reach them?" | [`leads/server.json`](leads/server.json) |
| **Jobs & Hiring** | 4 | "What roles are open right now, and where?" | [`jobs/server.json`](jobs/server.json) |
| **Marketplaces & Prices** | 6 | "What is listed, and what does it cost today?" | [`marketplaces/server.json`](marketplaces/server.json) |
| **Risk & Compliance** | 4 | "Is this name, domain, product or contract a problem?" | [`risk/server.json`](risk/server.json) |
| **News & Social** | 2 | "What is being said publicly, and when was it said?" | [`media/server.json`](media/server.json) |

---

### 1. Leads & Contacts

```
https://mcp.apify.com/?actors=snow_leo_data/google-maps-places-scraper-leads-emails,snow_leo_data/yellow-pages-scraper-bbb-europages-business-directory-leads,snow_leo_data/duckduckgo-scraper-local-business-maps-leads,snow_leo_data/no-website-local-business-leads-openstreetmap,snow_leo_data/contact-scraper-website-emails-phones-socials-lead-extractor
```

Five different indexes of the same world — Google's, Yelp/Apple's, the printed
directories, the open map, and the company's own website — so an agent that
comes up short in one can try another.

| Actor | What it returns | Measured |
|---|---|---|
| `snow_leo_data/google-maps-places-scraper-leads-emails` | Places from Google Maps, 56 columns, emails read from the business website | Google Maps stops near 150 places per search view; adaptive grid returned **766 places against 160** for `coffee` in Austin, 4.79x, in 42 s / 168 requests (12 Sep 2026) |
| `snow_leo_data/yellow-pages-scraper-bbb-europages-business-directory-leads` | Seven directories — Yellow Pages US/CA, BBB, Gelbe Seiten, PagineGialle, Europages, Hotfrog — in 38 shared columns | Every page a human can click on BBB gives **175 unique businesses**; bucketed queries returned **524** (runs `kt2dccRUXf2Itm2BL` = 175, `rKU71p8Dxq62dCgQ0` = 524) |
| `snow_leo_data/duckduckgo-scraper-local-business-maps-leads` | Local businesses from DuckDuckGo's index (Yelp + Apple Maps data), 44 fields, up to 5 review excerpts with text | Measured 16 Sep 2026 on 10 category+city pairs, with Google Maps swept to its own ceiling on each: of **164 businesses returned, 82 (50%) were not in Google Maps at all**. The `website` field was filled for **97.9%** of rows here against 79.7% in a Google Maps sample of 300 taken the same day |
| `snow_leo_data/no-website-local-business-leads-openstreetmap` | Businesses that have **no website**, from OpenStreetMap, 59 fields | Austin: **7,673 named businesses, 3,932 with no website at all**, one Overpass query, 80.5 s. Manchester UK: 5,905 / 4,261 in 13.4 s |
| `snow_leo_data/contact-scraper-website-emails-phones-socials-lead-extractor` | One row per website: emails, phones in E.164, socials across 31 platforms, address, hours | On 135 live business sites, home page only found an email on **31** sites; home page plus contact pages found one on **57** |

### 2. Jobs & Hiring

```
https://mcp.apify.com/?actors=snow_leo_data/greenhouse-workday-lever-ashby-ats-jobs-scraper,snow_leo_data/seek-scraper-jobstreet-jobsdb-australia-jobs-salaries,snow_leo_data/jobs-ch-scraper-swiss-switzerland-jobs,snow_leo_data/the-muse-scraper-remote-company-jobs-board
```

One tool for jobs straight from the employer's own ATS, and three for the job
boards that dominate a region. All four return the same kind of row, so an agent
can compare a Swiss board against a US careers page without reshaping anything.

| Actor | What it returns | Measured |
|---|---|---|
| `snow_leo_data/greenhouse-workday-lever-ashby-ats-jobs-scraper` | Jobs read live from 20 applicant tracking systems — Greenhouse, Workday, Lever, Ashby, SmartRecruiters, Oracle Cloud, BrassRing, UKG and twelve more | **59,185 jobs in one run**; **1,045 company boards built in**, so an empty input still works. $0.99 per 1,000 where others in the niche charge $1.30, $2.50 and $4.00 |
| `snow_leo_data/seek-scraper-jobstreet-jobsdb-australia-jobs-salaries` | SEEK AU/NZ, JobStreet MY/SG/PH/ID, JobsDB HK/TH — 8 markets, 41 fields | The public API stops at **500 jobs per query** (page 6 at 100 rows returns an empty list); this Actor returned **1,500 unique jobs in 120 s**, zero duplicates |
| `snow_leo_data/jobs-ch-scraper-swiss-switzerland-jobs` | jobs.ch, 38 fields, full advert text, direct apply URL, Swiss workload percentage, coordinates | **46,121 jobs live on jobs.ch**; page 101 returns HTTP 422, so one query caps at **2,000**. Measured **2,400 unique jobs in 64 s**, zero duplicates |
| `snow_leo_data/the-muse-scraper-remote-company-jobs-board` | The Muse, 27 fields, the entire advert body inline | **411,813 jobs** on the source; page 100 returns HTTP 400 so one query caps at **1,980**. Measured **2,060 unique jobs in 176 s**, zero duplicates |

### 3. Marketplaces & Prices

```
https://mcp.apify.com/?actors=snow_leo_data/amazon-product-scraper-prices-asin-bestsellers,snow_leo_data/shopify-scraper-products-inventory-variants-sku-prices-store,snow_leo_data/apple-app-store-scraper-reviews-ratings-aso-ios-apps,snow_leo_data/google-play-store-scraper-apps-reviews-charts,snow_leo_data/airbnb-scraper-listings-prices-availability-calendar-reviews,snow_leo_data/redfin-scraper-real-estate-listings-rentals-prices-sold
```

Every tool here returns a priced listing out of somebody's catalogue — products,
apps, stays, homes — and every one of them is built around getting past that
catalogue's own result ceiling.

| Actor | What it returns | Measured |
|---|---|---|
| `snow_leo_data/amazon-product-scraper-prices-asin-bestsellers` | amazon.com search, product pages and Best Sellers: prices, list price, discount, rating, stock, seller, specs, BSR, ASIN | **One Amazon search stops at 306 products** for `wireless earbuds` while Amazon's own header claimed over 20,000. Six price bands returned 96 products, **96 unique, zero overlap** |
| `snow_leo_data/shopify-scraper-products-inventory-variants-sku-prices-store` | Any Shopify storefront: 42 fields per product, every variant, price, compare-at, SKU, barcode, stock, collection | On 47 live storefronts, 14 refuse `/products.json` on their own domain; reading the shop's Shopify origin recovered **10 of those 14** — **43 stores readable instead of 33** |
| `snow_leo_data/apple-app-store-scraper-reviews-ratings-aso-ios-apps` | App Store reviews and the full store card, per storefront, across 59 Apple storefronts | Apple caps at **500 reviews per storefront per sort order** (page 11 returns HTTP 400). Opening both sort windows gave **937 unique reviews** on one app, only 63 shared. Notion on 12 Sep 2026: 90,067 ratings in USD in the US storefront, 50,062 in JPY in the Japanese one |
| `snow_leo_data/google-play-store-scraper-apps-reviews-charts` | Google Play reviews, app details, keyword search, top charts, developer listings, similar apps — 6 modes | Play keeps reviews **per language, and the piles do not overlap**. `com.spotify.music`, 13 Sep 2026: 18 languages x 600 = **10,800 distinct review IDs, 0 duplicates between languages** |
| `snow_leo_data/airbnb-scraper-listings-prices-availability-calendar-reviews` | Airbnb listings, details, the day-by-day availability calendar with occupancy rates, and reviews | Airbnb search hands out at most **270 rows per query** which contain **227 distinct listings**. Paris, 13 Sep 2026: flat pagination 257 listings from 7 queries; adaptive map grid **1,916 from 63 queries — 7.46x**, in 117 s |
| `snow_leo_data/redfin-scraper-real-estate-listings-rentals-prices-sold` | Redfin by city, county, neighborhood or ZIP: price, beds, baths, area, year, DOM, MLS number and description, agent, coordinates; property card adds parcel, tax rate, schools, climate risk, permits, zoning | Redfin's search endpoint **has no pagination** — `page_number=2` returns page 1 byte for byte. Redfin's own "Download All" CSV export stops at **350** listings |

### 4. Risk & Compliance

```
https://mcp.apify.com/?actors=snow_leo_data/ofac-sdn-eu-un-sanctions-list-screening,snow_leo_data/cve-scraper-nvd-kev-epss-vulnerability-database,snow_leo_data/dns-records-mx-whois-lookup-dmarc-spf-domain-monitor,snow_leo_data/government-tenders-scraper-ted-sam-gov-procurement
```

Four checks an agent runs before it recommends doing business with someone: is
the name sanctioned, is the software exploitable, is the domain real and able to
receive mail, and is there a public contract behind it.

| Actor | What it returns | Measured |
|---|---|---|
| `snow_leo_data/ofac-sdn-eu-un-sanctions-list-screening` | US Treasury OFAC SDN, the EU consolidated list and the UN Security Council consolidated list, joined, with which authorities list each name | **26,633 records** against the 19,388 in OFAC alone — 37% more. OFAC 19,388, EU 6,234, UN 1,011. **4,370 listed by two or more authorities, 1,693 by all three.** No API key, no registration, no proxy |
| `snow_leo_data/cve-scraper-nvd-kev-epss-vulnerability-database` | Every CVE from the NIST National Vulnerability Database, joined with CISA KEV and EPSS | **389,995 CVEs** — the whole NVD catalo

Lo que la gente pregunta sobre mcp-servers-snowleo

¿Qué es MagzhanSan/mcp-servers-snowleo?

+

MagzhanSan/mcp-servers-snowleo es mcp servers para el ecosistema de Claude AI. MCP servers exposing Snow Leo Data web-data tools on Apify Tiene 0 estrellas en GitHub y su última actualización registrada es del 2026-09-17.

¿Cómo se instala mcp-servers-snowleo?

+

Puedes instalar mcp-servers-snowleo clonando el repositorio (https://github.com/MagzhanSan/mcp-servers-snowleo) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

¿Es seguro usar MagzhanSan/mcp-servers-snowleo?

+

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¿Quién mantiene MagzhanSan/mcp-servers-snowleo?

+

MagzhanSan/mcp-servers-snowleo es mantenido por MagzhanSan. La última actividad registrada en GitHub es del 2026-09-17, con 0 issues abiertos.

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