Chrome Extension Intelligence — CWS Database, Analytics & MCP

Search and analyze 262,000+ Chrome Web Store extensions instantly. AI semantic search, 90-day historical tracking, competitive intelligence, developer analytics — all from a pre-built database with millisecond responses. Connect via REST API or use the built-in MCP server to give your AI agent direct access to Chrome extension data.

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Why not a real-time scraper?

Most Chrome Web Store scrapers fetch data on demand — slow, frequently blocked by Google, and with no historical context. CWS Intelligence works differently: all data is pre-indexed and continuously updated, so every query returns in milliseconds with history already attached.

	Real-time CWS scrapers	CWS Intelligence
Response time	5–30 seconds	Milliseconds
Blocking / downtime risk	High	None
Historical data (users, ratings, versions)	❌	✅ Weekly snapshots, growing over time
AI semantic search	❌	✅
Developer profiles & portfolio	❌	✅
Trending detection	❌	✅ 7 / 30 / 90-day growth
Works as MCP server	❌	✅

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What it does

This Actor provides API access to a continuously updated Chrome Web Store database. Key capabilities:

• Keyword search with filters — category, min users, min rating, sorting
• AI semantic search — find extensions by meaning, not just keywords (e.g., "tools that help organize browser tabs")
• Extension details — full metadata: permissions, screenshots, description, manifest version
• Historical tracking — user count, rating, and version changes over time (up to 90 days)
• Developer profiles — aggregated stats and full extension lists per developer
• Trending extensions — fastest-growing by user count over 7 / 30 / 90-day periods
• Side-by-side comparison — compare 2–5 extensions at once
• Similar extensions — AI-powered recommendations based on description embeddings

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Use cases

Find market gaps before building Search a category, filter by user count, sort by last-updated date — identify extensions with 50K+ users that haven't been updated in 2+ years. These are your displacement opportunities or acquisition targets.

Track a competitor before launching Pull 90-day history for any extension to see whether it's growing, plateauing, or declining. Know their trajectory before you enter the market.

Validate demand without building Use semantic search to find all extensions solving a problem you're considering. If the top result has 200K users and 2 stars — that's your market signal.

Feed your AI agent with extension intelligence Connect via MCP and let Claude, GPT-4o, or any AI agent query the database directly. Ask: "Which Notion extensions are growing fastest this month?" and get a structured answer in seconds.

Spot brand squatters and copycats Search your brand name, filter by recently created — catch copycat extensions before they steal your traffic.

Build developer prospecting lists Search developers by name or keyword, get aggregated stats across their entire portfolio — useful for partnership outreach or acquisition research.

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Data freshness

The entire database is re-crawled once per week — every extension gets a fresh snapshot on the same cadence.

• Total extensions indexed: 262,000+
• Update frequency: Weekly (full re-crawl of all extensions)
• History depth: Growing weekly — 1 week of snapshots now, expanding automatically over time
• Coverage: All public Chrome Web Store extensions

The history window grows with each passing week. The longer the Actor runs, the richer the trend data you can query.

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Input parameters

Parameter	Type	Description
action	string	Required. One of the actions listed below
query	string	Search text (keyword or natural language for semantic search)
extensionId	string	32-char extension ID
extensionIds	string[]	Array of 2–5 extension IDs (for compare_extensions)
developerName	string	Developer name (exact for get_developer, partial for search_developers)
category	string	Category slug filter (e.g., productivity/tools)
minUsers	integer	Minimum user count filter
minRating	number	Minimum rating filter (0–5)
sort	string	Sort by: users, rating, name, updated, created, reviews, size
sortDirection	string	asc or desc
limit	integer	Results per page (1–100, default 20)
page	integer	Page number
historyDays	integer	Limit history to last N days (bounded by available snapshot depth)
trendingPeriod	string	7d, 30d, or 90d

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Actions

Action	Description	Required params
search	Keyword search with filters and sorting	—
semantic_search	AI search by meaning	query
get_extension	Full extension details	extensionId
get_extension_history	Metric snapshots over time	extensionId
get_developer	Developer profile + extensions	developerName
search_developers	Search developers	—
get_categories	All categories with counts	—
get_stats	Database statistics	—
get_similar	AI-powered similar extensions	extensionId
get_trending	Fastest-growing extensions	—
compare_extensions	Side-by-side comparison	extensionIds

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Output

Results are pushed to the default dataset. Structure depends on the action:

• search / semantic_search / get_trending / get_similar — array of extension objects
• get_extension — single extension object with full metadata
• get_extension_history — snapshots array + text field changes
• get_developer — developer profile with aggregated stats and extensions list
• search_developers — array of developer profiles
• get_categories — array of categories with extension counts
• get_stats — database summary (total extensions, last update, coverage)
• compare_extensions — array of extension objects with 30-day history

For paginated actions, metadata (total, page, limit) is stored in the key-value store under the metadata key.

Sample output

search / get_trending / get_similar return extension objects:

{
  "id": "cjpalhdlnbpafiamejdnhcphjbkeiagm",
  "name": "AdBlock — best ad blocker",
  "developer": "AdBlock",
  "users": 65000000,
  "rating": 4.5,
  "rating_count": 280000,
  "version": "6.8.0",
  "category": "productivity/tools",
  "manifest_version": 3,
  "last_updated": "2026-03-15",
  "permissions": ["storage", "declarativeNetRequest"]
}

get_extension_history returns metric snapshots:

{
  "extension_id": "cjpalhdlnbpafiamejdnhcphjbkeiagm",
  "snapshots": [
    { "date": "2026-03-01", "users": 64200000, "rating": 4.5, "version": "6.7.9" },
    { "date": "2026-03-15", "users": 65000000, "rating": 4.5, "version": "6.8.0" }
  ],
  "growth_30d": 800000,
  "growth_pct_30d": 1.25
}

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Pricing

Pay only for what you use. Most research sessions cost less than $1.

A typical workflow — 10 keyword searches, 5 extension detail lookups, 2 history checks — costs around $0.25. The pricier AI operations (semantic search, similar extensions) use embedding models at $0.04/call, still far cheaper than any manual research time.

Event	Price
Database Stats	$0.001
Categories List	$0.002
Extension Details	$0.005
Developer Profile	$0.010
Keyword Search	$0.015
Developer Search	$0.015
Compare Extensions	$0.020
Extension History	$0.030
Trending Extensions	$0.030
AI Semantic Search	$0.040
Similar Extensions (AI)	$0.040

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MCP Server (Standby Mode)

This Actor doubles as an MCP server when running in Standby mode. AI agents connect to the /mcp endpoint using the Model Context Protocol to query the database programmatically.

Available MCP tools: search_extensions, semantic_search, get_extension, get_extension_history, get_developer, search_developers, get_categories, get_stats, get_similar, get_trending, compare_extensions

Connect from Claude Desktop

{
  "mcpServers": {
    "cws-intelligence": {
      "type": "url",
      "url": "https://aross--cws-intelligence.apify.actor/mcp?token=***"
    }
  }
}

Connect from Cursor

{
  "mcpServers": {
    "cws-intelligence": {
      "type": "url",
      "url": "https://aross--cws-intelligence.apify.actor/mcp?token=***",
      "headers": {
        "Authorization": "Bearer YOUR_APIFY_TOKEN"
      }
    }
  }
}

Connect from Windsurf

{
  "mcpServers": {
    "cws-intelligence": {
      "serverUrl": "https://aross--cws-intelligence.apify.actor/mcp?token=***"
    }
  }
}

Connect from any MCP-compatible client

• Endpoint: https://aross--cws-intelligence.apify.actor/mcp?token=***
• Auth: Bearer token (your Apify API token)
• Protocol: Model Context Protocol over HTTP/SSE

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Examples

Find tab management extensions with 10K+ users

{
  "action": "search",
  "query": "tab manager",
  "minUsers": 10000,
  "sort": "users"
}

Find underserved extensions: high users, low rating

{
  "action": "search",
  "category": "productivity/tools",
  "minUsers": 50000,
  "sort": "rating",
  "sortDirection": "asc"
}

Semantic search for privacy tools

{
  "action": "semantic_search",
  "query": "tools that block trackers and protect browsing privacy"
}

Track an extension's growth over 90 days

{
  "action": "get_extension_history",
  "extensionId": "cjpalhdlnbpafiamejdnhcphjbkeiagm",
  "historyDays": 90
}

Compare top ad blockers side by side

{
  "action": "compare_extensions",
  "extensionIds": [
    "cjpalhdlnbpafiamejdnhcphjbkeiagm",
    "gighmmpiobklfepjocnamgkkbiglidom"
  ]
}

Get fastest-growing extensions this week

{
  "action": "get_trending",
  "trendingPeriod": "7d",
  "limit": 10
}

Find all extensions by a prolific developer

{
  "action": "get_developer",
  "developerName": "Google LLC"
}

Find extensions similar to a known one

{
  "action": "get_similar",
  "extensionId": "cjpalhdlnbpafiamejdnhcphjbkeiagm"
}