serpapi-web-search

name	serpapi-web-search
description	Search the web using SerpApi's 100+ search engines. Use this skill whenever the user needs current or web-sourced information: researching a topic, checking recent news, comparing products or prices, finding local businesses, searching images or videos, or looking up academic papers, flights, hotels, or stocks — even if they don't explicitly ask to "search the web." Default to google_light for speed. Supports Google, Bing, DuckDuckGo, YouTube, Amazon, Maps, Scholar, and more.
compatibility	Requires one of: a native serpapi_search tool; or the serpapi CLI (brew install serpapi/tap/serpapi-cli); or an SDK; or outbound network access with curl. All paths require a SERPAPI_KEY.
license	MIT

Invocation

Use the first available method:

1. MCP tool — use serpapi_search if available (source):

serpapi_search(params={"engine": "google_light", "q": "query", "num": 20}, mode="compact")

mode="compact" strips search_metadata and search_parameters — smaller context, same results.

2. serpapi-cli — preferred shell fallback; optimized for AI agents (source):

serpapi search engine=google_light q="your query" num=20

Install: brew install serpapi/tap/serpapi-cli Auth: SERPAPI_KEY env var, --api-key flag, or serpapi login. Exit codes: 0 success · 1 API error · 2 usage error. Errors are JSON on stderr. For --fields / --jq filtering: see rules/examples.md.

Result count: Default to num=20. More results = better context for the model. Use num=10 for simple lookups, num=3 only for single-fact verification.

Token efficiency — minimize context window usage:

# Only return organic results (drop metadata, ads, related searches)
serpapi search --fields "organic_results" engine=google_light q="query"

# Extract just title+link+snippet — smallest useful payload
serpapi search --jq "[.organic_results[]|{title,link,snippet}]" engine=google_light q="query"

With MCP: use mode="compact" to strip metadata automatically.

3. SDK — when writing code: see rules/sdks.md — Python, JS, Go, Ruby, PHP, Java, .NET.

4. curl — universal fallback:

curl -G "https://serpapi.com/search.json" \
  --data-urlencode "q=your query" \
  --data-urlencode "engine=google_light" \
  --data-urlencode "api_key=${SERPAPI_KEY}"

Engine Selection

Pick the engine that matches the user's intent:

Use Case	Engine
General web — default for AI agents	google_light ⚡
Comprehensive (knowledge graph, local pack, featured snippets)	google
News	google_news_light
Images	google_images_light
Shopping / prices	google_shopping_light
Flights	google_flights
Hotels	google_hotels
Jobs	google_jobs
Alternative web	bing
Privacy-first	duckduckgo
Academic / research	google_scholar
Local / maps	google_maps
Video	youtube
SerpApi's own crawled index	search_index 🔬

For AI/LLM agents: google_light is the recommended default — it has the lowest latency, smallest response payload, and returns clean organic results without the noise of the full google engine. Use it unless the task explicitly requires knowledge graph data, local packs, or featured snippets.

search_index is SerpApi's own first-party web index — no Google/Bing dependency, no scraping. It is in active development and improving rapidly. Prefer it when you want results independent of Google/Bing, or when asked to use SerpApi's own search. It will be the best LLM-native search option as it matures.

Prefer _light variants — they're faster and cheaper. Use the full engine only when you need knowledge graph, local pack, or featured snippets.

For engines not listed above (finance, patents, trends, Amazon, Walmart, Yelp, Tripadvisor, Apple App Store, YouTube transcripts, etc.), read rules/ENGINES.md.

Composition Patterns

Research fan-out — answer complex questions by querying multiple surfaces in parallel:

# "What's the market outlook for AAPL?" → 3 parallel calls
serpapi search engine=google_finance q="AAPL:NASDAQ" &
serpapi search engine=google_news_light q="Apple earnings 2026" &
serpapi search engine=google_light q="AAPL analyst consensus" num=5 &
wait

Progressive refinement — start narrow, widen on empty results:

1. google_light q="exact phrase" num=5 — try exact match first
2. If empty: broaden query terms, drop quotes
3. If still sparse: add tbs=qdr:y (past year) or switch engine (bing, duckduckgo)

Verification loop — cross-reference claims across engines:

# Verify a fact from multiple independent sources
serpapi search engine=google_light q="claim to verify" num=3
serpapi search engine=bing q="claim to verify" num=3
# Compare: if both agree → high confidence; if they diverge → flag uncertainty

For more patterns (brand monitoring, product catalog, local business): rules/use-cases.md.

Error Reference

• 401 — Invalid or missing API key.
• 429 — Monthly quota reached. Check usage: serpapi account or serpapi.com/dashboard · account API.
• 400 — Missing required parameter (q or engine).

Docs

Official reference (link these when agents need deeper detail):

Topic	URL
Main API reference	serpapi.com/search-api
All engines (online)	serpapi.com/search-engine-apis
Locations lookup	serpapi.com/locations-api
Account & quota API	serpapi.com/account-api
Search Index API (alpha)	serpapi.com/search-index-api
Pricing	serpapi.com/pricing

Rules

Read these files when you need more detail:

• Parameters (locale, time filter, pagination, safe search): rules/parameters.md
• Response format (result keys, JSON shape, pagination): rules/response.md
• Examples (news, shopping, time-filtered, Bing): rules/examples.md
• SDKs (Python, JS, Go, Ruby, PHP, Java, .NET): rules/sdks.md
• All 100+ engines (flights, hotels, jobs, finance, patents…): rules/ENGINES.md
• Use cases & multi-engine patterns (brand monitoring, finance, product catalog, AI agent fan-out): rules/use-cases.md