Real-time web search with AI-powered agents that understand intent and return structured data
Nimble Search delivers real-time web search powered by Web Search Agents (WSAs) that understand query intent and return structured, agent-ready data. Unlike generic search engines, WSAs navigate websites directly to extract deeper insights and format results for seamless AI integration.Perfect for AI agents, research automation, competitive intelligence, content monitoring, and any application that needs real-time web data with structured outputs.
{ "total_results": 5, "answer": "Recent developments in AI agents include autonomous decision-making capabilities, improved tool use, and better integration with external APIs. Notable advances include multi-agent collaboration frameworks and enhanced reasoning capabilities...", "results": [ { "title": "AI Agents: The Next Frontier in 2026", "description": "Exploring the latest breakthroughs in autonomous AI agents...", "url": "https://example.com/ai-agents-2026", "content": "# AI Agents: The Next Frontier\n\nAI agents have evolved significantly...", "metadata": { "position": 1, "entity_type": "OrganicResult", "country": "US", "locale": "en" } }, { "title": "Autonomous Agents and Tool Use", "description": "How modern AI agents interact with external tools and APIs...", "url": "https://example2.com/agent-tools", "content": "# Autonomous Agents and Tool Use\n\nThe ability to use tools...", "metadata": { "position": 2, "entity_type": "OrganicResult", "country": "US", "locale": "en" } }, {...} ], "request_id": "84f08ac1-bb5f-4b6f-8447-2d21cb930416"}
Choose the right mode\ • Use Fast Mode (deep_search: false) for URL
discovery and quick answers with concise, token-efficient results perfect for
agentic loops.\ • Use Deep Search (deep_search: true, default) when you
need comprehensive full-page content for deeper analysis.
Get search results without extracting full content (1 credit per search). Perfect for high-volume operations, URL discovery, and cost-conscious scenarios where you only need titles, snippets, and links.
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from nimble_python import Nimblenimble = Nimble(api_key="YOUR-API-KEY")result = nimble.search( query="best web scraping tools 2026", max_results=10, deep_search=False)for item in result.results: print(f"{item.title}: {item.url}")
Deep Search with content extraction
Extract full content from search results (1 credit + 1 per page). Retrieves complete page content for in-depth analysis, feeding LLMs, or building comprehensive knowledge bases.
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from nimble_python import Nimblenimble = Nimble(api_key="YOUR-API-KEY")result = nimble.search( query="python web scraping tutorial", max_results=5, deep_search=True, output_format="markdown")for item in result.results: print(f"Title: {item.title}") print(f"URL: {item.url}") print(f"Content: {item.content[:200]}...") print("---")
Search with LLM answer
Get an AI-generated answer based on search results. Returns an instant summary with inline citations, perfect for Q&A systems, chatbots, and research assistants.
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from nimble_python import Nimblenimble = Nimble(api_key="YOUR-API-KEY")result = nimble.search( query="what are the benefits of TypeScript over JavaScript", max_results=10, include_answer=True)print("AI Answer:")print(result.answer)print("\nSources:")for item in result.results: print(f"- {item.title}: {item.url}")
Time-based filtering
Filter results by recency using time_range or specify exact date ranges. Essential for news monitoring, tracking recent developments, or analyzing historical data within specific timeframes.
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from nimble_python import Nimblenimble = Nimble(api_key="YOUR-API-KEY")# Filter by time rangeresult = nimble.search( query="AI news", max_results=20, time_range="week")# Or use specific date rangeresult = nimble.search( query="machine learning advances", max_results=15, start_date="2026-01-01", end_date="2026-01-31")print(result)
Domain filtering
Filter results to specific domains or exclude unwanted ones. Focus on trusted sources, exclude noise (social media, ads), or search within curated lists of authoritative sites.
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from nimble_python import Nimblenimble = Nimble(api_key="YOUR-API-KEY")# Only search within specific domainsresult = nimble.search( query="python async patterns", max_results=10, include_domains=["github.com", "stackoverflow.com", "docs.python.org"])# Or exclude specific domainsresult = nimble.search( query="web scraping tutorial", max_results=10, exclude_domains=["pinterest.com", "youtube.com"])print(result)
Document type filtering
Search for specific document types like PDFs, spreadsheets, or presentations (only works with focus: "general"). Perfect for academic research, finding reports, whitepapers, or structured data files.
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from nimble_python import Nimblenimble = Nimble(api_key="YOUR-API-KEY")# Search for PDF documentsresult = nimble.search( query="machine learning research papers", max_results=10, focus="general", content_type=["pdf"])# Search for multiple document typesresult = nimble.search( query="financial reports 2026", max_results=15, focus="general", content_type=["pdf", "xlsx", "docx"])# Use semantic groups for broader filteringresult = nimble.search( query="quarterly earnings", max_results=10, focus="general", content_type=["documents", "spreadsheets"])print(result)
content_type only works with focus: "general". Supported formats: pdf, docx, xlsx, pptx, and semantic groups: documents, spreadsheets, presentations.
Topic modes route your searches to specialized sources optimized for different use cases. Each mode uses dedicated Web Search Agents to retrieve the most relevant results.
Pre-defined focus modes automatically route your search to specialized Nimble Web Search Agents (WSA) based on your query type. Simply specify the mode that matches your use case.
For advanced use cases, you can explicitly specify which search agents to use by passing an array of subagent names to the focus parameter. This gives you full control over data sources and enables mixing agents from different focus modes.Example:
