Web Search
Multi-engine web search with advanced filtering, ranking, and result aggregation capabilities.
Search multiple search engines simultaneously with advanced filtering, ranking algorithms, and comprehensive result processing for research and data collection.
Features
- Multi-engine search support (Google, Bing, DuckDuckGo, Academic)
- Advanced query filtering and ranking
- Result deduplication and relevance scoring
- Content type and domain filtering
- Date range and language restrictions
Connector Options
The node uses reusable connector configuration that applies to all search operations:
| Parameter | Type | Required | Description |
|---|---|---|---|
apiKeys | Object | Yes | API keys for search engines (google, bing, etc.) |
defaultEngine | TEXT | No | Default search engine when not specified |
maxResults | INT | No | Default maximum results per search (default: 50) |
rateLimit | INT | No | Requests per minute limit (default: 60) |
Methods
webSearch
Execute multi-engine web searches with advanced filtering and ranking.
| Parameter | Type | Required | Description |
|---|---|---|---|
query | TEXT | Yes | Search query string |
engines | Array | No | Search engines to use: google, bing, duckduckgo, academic |
maxResults | INT | No | Maximum number of results to return |
filters | Object | No | Search filters and restrictions |
ranking | TEXT | No | Result ranking method: relevance, date, authority |
{
"query": "machine learning python tutorials",
"engines": ["google", "bing", "duckduckgo"],
"maxResults": 50,
"filters": {
"dateRange": "past_year",
"contentType": ["article", "tutorial"],
"language": "en",
"domain": ["github.com", "stackoverflow.com"]
},
"ranking": "relevance"
}Output:
results(Array) - Search results with metadatatotalResults(Number) - Total number of results foundsearchTime(Number) - Search execution time in millisecondsengines(Array) - Engines used and their response statusquery(Object) - Processed query information
academicSearch
Search academic databases and research repositories for scholarly content.
| Parameter | Type | Required | Description |
|---|---|---|---|
query | TEXT | Yes | Academic search query |
publicationType | Array | No | Publication types: journal, conference, book, thesis |
dateRange | TEXT | No | Publication date range |
citationThreshold | INT | No | Minimum citation count |
subject | Array | No | Subject areas to search within |
{
"query": "natural language processing transformers",
"publicationType": ["journal", "conference"],
"dateRange": "past_5_years",
"citationThreshold": 10,
"subject": ["computer_science", "artificial_intelligence"]
}newsSearch
Search news sources and current events with real-time filtering.
| Parameter | Type | Required | Description |
|---|---|---|---|
query | TEXT | Yes | News search query |
sources | Array | No | Specific news sources to search |
sentiment | TEXT | No | Filter by sentiment: positive, negative, neutral |
freshness | TEXT | No | Content freshness: hour, day, week, month |
{
"query": "sustainable energy technology",
"sources": ["reuters", "bloomberg", "techcrunch"],
"sentiment": "neutral",
"freshness": "week"
}Search Filters
Content Filtering
| Filter | Type | Description | Example Values |
|---|---|---|---|
dateRange | TEXT | Time period for results | "past_day", "past_week", "past_month", "past_year" |
contentType | Array | Type of content to find | ["article", "blog", "news", "tutorial", "research"] |
language | TEXT | Content language | "en", "es", "fr", "de", "zh" |
domain | Array | Specific domains to include | ["github.com", "stackoverflow.com", "arxiv.org"] |
excludeDomains | Array | Domains to exclude | ["pinterest.com", "facebook.com"] |
Quality Filters
| Filter | Type | Description | Example Values |
|---|---|---|---|
minWordCount | INT | Minimum content length | 500 |
authorityScore | FLOAT | Domain authority threshold | 0.7 |
readabilityLevel | TEXT | Content reading level | "basic", "intermediate", "advanced" |
contentQuality | TEXT | Quality assessment | "high", "medium", "any" |
Result Processing
Ranking Algorithms
Relevance Ranking:
- Query term frequency and positioning
- Title and header matching weights
- Domain authority scoring
- Content freshness factors
- User engagement signals
Authority Ranking:
- Domain reputation scores
- Backlink analysis
- Content creator credibility
- Publication venue quality
- Citation counts (academic content)
Date Ranking:
- Publication or update timestamps
- Content freshness scoring
- Trend relevance analysis
- Temporal query matching
Deduplication
- URL normalization and comparison
- Content similarity detection
- Title and description matching
- Domain clustering analysis
- Canonical URL resolution
Performance Optimization
Caching Strategy
{
"query": "artificial intelligence trends",
"engines": ["google", "bing"],
"caching": {
"enabled": true,
"ttl": 3600,
"keyFactors": ["query", "filters", "engines"],
"compression": true
}
}Batch Operations
{
"batchSearch": {
"queries": [
"machine learning applications",
"deep learning frameworks",
"neural network architectures"
],
"engines": ["google", "academic"],
"maxResults": 30,
"parallel": true,
"rateLimiting": {
"requestsPerMinute": 30,
"delayBetweenRequests": 2000
}
}
}Error Handling
Common Error Responses
| Error Type | Cause | Resolution |
|---|---|---|
QUOTA_EXCEEDED | API limit reached | Wait for quota reset or use different engine |
INVALID_QUERY | Malformed search query | Check query syntax and special characters |
ENGINE_UNAVAILABLE | Search engine down | Use alternative engines or retry later |
RATE_LIMITED | Too many requests | Implement request throttling |
Error Response Format
{
"success": false,
"error": {
"type": "QUOTA_EXCEEDED",
"message": "Daily search quota exceeded for Google Search API",
"engine": "google",
"retryAfter": 3600,
"suggestions": [
"Use alternative search engines",
"Wait for quota reset",
"Upgrade API plan"
]
}
}Usage Examples
Basic Web Search
{
"query": "Python web scraping tutorial",
"engines": ["google", "bing"],
"maxResults": 20,
"filters": {
"contentType": ["tutorial", "documentation"],
"language": "en"
}
}Academic Research Search
{
"query": "quantum computing algorithms",
"engines": ["academic"],
"maxResults": 25,
"filters": {
"publicationType": ["journal", "conference"],
"dateRange": "past_3_years",
"citationThreshold": 5
},
"ranking": "authority"
}Competitive Intelligence
{
"query": "Company XYZ product launches 2024",
"engines": ["google", "bing"],
"maxResults": 100,
"filters": {
"dateRange": "past_year",
"contentType": ["news", "press_release"],
"domain": ["techcrunch.com", "venturebeat.com", "bloomberg.com"]
},
"ranking": "date"
}Integration Patterns
With Data Analysis Tools
Search for data and automatically process results for insights and pattern detection.
With File System Tools
Save search results to structured files for offline analysis and archival.
With Web Scraping Tools
Use search results as input for targeted content extraction workflows.
Best Practices
Query Optimization
- Use specific, targeted keywords
- Include relevant context terms
- Utilize search operators when available
- Test queries across multiple engines
Result Quality
- Set appropriate quality filters
- Use domain restrictions wisely
- Balance quantity vs. relevance
- Monitor and adjust ranking algorithms
Resource Management
- Implement proper rate limiting
- Cache frequently used searches
- Monitor API quota usage
- Use batch operations efficiently
Ethical Considerations
- Respect search engine terms of service
- Implement appropriate delays between requests
- Avoid overwhelming target websites
- Consider data privacy and user consent
Getting Started
- Configure API keys for desired search engines
- Set default search parameters and rate limits
- Test basic queries with different engines
- Implement error handling and retry logic
- Monitor search performance and optimization