The search API
that thinks.
One API call. 11 federated search backends, 8-signal neural ranking, 5-layer content extraction, and token-budgeted context with evidence graphs — in under 200ms.
Why developers choose HyperSearchX
The only search API with federated backends, neural ranking, and cross-session learning — features no competitor offers at any price.
See comparisonCapabilities no other search API has
Every algorithm was designed from scratch to solve a real gap in the AI search stack — not a wrapper around an existing tool.
11-Backend Search Federation
Fan out a single query across SearXNG, Brave, GitHub, Reddit, HackerNews, StackOverflow, YouTube, Wikipedia, ArXiv, Bing, and DuckDuckGo — simultaneously. Adaptive Backend Selector picks the right mix per query intent. No other search API comes close.
HyperFusion Neural Ranking
8-signal ranking engine: BM25 lexical match + semantic similarity + temporal decay + domain authority + evidence density + source diversity + content depth + cross-source consensus. Results are measurably better than single-signal ranking — every time.
5-Layer CEP Content Extraction
Content Extraction Protocol: CSS selectors → Readability algorithm → Headless JS rendering → PDF parsing → Screenshot OCR. Every page — SPAs, paywalled content, PDFs — returns clean, structured text. Zero pages escape extraction.
QATBE Token Budget Control
Query-Aware Token-Budgeted Extraction scores every content segment with BM25 then solves a greedy knapsack to pack maximum relevance into your exact LLM context window. You always get the most useful content — not just the first N characters.
Deep Research Pipeline
AMRS multi-agent research swarm: 4 specialist agent types communicate over async channels, synthesise findings, and generate full evidence graphs with every claim traced to a source. Auto-generate citations in APA, IEEE, BibTeX, or Chicago.
Production Resilience
Circuit breakers, bulkhead isolation, adaptive rate limiting, and latency prediction across all backends. Automatic failover, retry-and-refine with 5-checkpoint self-correction, and 99.9% uptime SLA on Pro and Enterprise plans.
YouTube & Social Intelligence
VideoFusion ranking for YouTube: transcript extraction, comment sentiment, teaching quality scoring. Native Reddit, HackerNews, and StackOverflow backends with community signal weighting. Social search no other API provides.
PIE Cross-Session Learning
Persistent Intelligence Engine tracks source trust, failure patterns, and query predictions across sessions via SQLite. HyperSearchX gets smarter with every query your application makes — improving result quality automatically over time.
MCP Protocol Native
First-class Model Context Protocol support. Expose all 17 algorithms as MCP tools to Claude, GPT-4, and any LLM with tool use. Structured, schema-validated outputs are AI-consumption-ready out of the box — no post-processing needed.
How it works
Six stages. Under 200ms. Every result traced back to its source with an evidence graph.
Query Analysis
~2msYour query is fingerprinted, classified by intent, scored for complexity, and expanded with semantic variants. The system chooses the optimal backend mix before a single network call is made.
Multi-Backend Federation
~120msThe Adaptive Backend Selector fans your query across up to 11 sources in parallel — SearXNG, Brave, GitHub, Reddit, StackOverflow, YouTube, and more. Circuit breakers handle backend failures invisibly.
HyperFusion Ranking
~18msResults are scored on 8 signals: BM25 lexical match, semantic similarity, temporal freshness, domain authority, evidence density, source diversity, content depth, and cross-source consensus.
CEP Content Extraction
~40msTop-ranked URLs are deep-extracted via the Content Extraction Protocol: CSS selectors → Readability algorithm → Headless JS rendering → PDF parsing → Screenshot OCR. Zero pages escape clean extraction.
Token Budget Control
~5msExtracted content is segmented, BM25-scored for query relevance, then packed into your token budget via greedy knapsack. You always get the most relevant content that fits your LLM context window.
AI-Ready Response
Total < 200msThe final response includes ranked results, extracted content within your budget, an evidence graph tracing every claim to a source, and auto-generated citations in APA, IEEE, BibTeX, or Chicago format.
First result in 60 seconds
Install the SDK, paste your key, ship. Real multi-source search with zero boilerplate.
1import { HyperSearchX } from "@hypersearchx/sdk";23const hsx = new HyperSearchX({4 apiKey: process.env.HSX_API_KEY!,5 baseUrl: "https://api.hypersearchx.zuhabul.com",6});78// Multi-source federated search9const results = await hsx.search("rust async programming", {10 backends: ["searxng", "brave", "github", "stackoverflow"],11 maxResults: 10,12 tier: "summary", // key_facts | summary | detailed | complete13 tokenBudget: 2000, // QATBE greedy-knapsack packing14 ranking: "hyperfusion" // 8-signal neural ranking15});1617console.log(results.items[0].title);18console.log(results.meta.tokensUsed); // always within budget19console.log(results.evidenceGraph); // citations + trust scores2021// Deep-extract any URL22const page = await hsx.extract("https://docs.rs/tokio", {23 format: "markdown",24 tokenBudget: 4096,25 layer: "readability", // css | readability | headless | pdf | ocr26});
The async book covers futures, async/await syntax, Tokio runtime, and concurrent task management...
A runtime for writing reliable, asynchronous, and slim applications. Stars: 28k...
Accepted answer (1.2k votes): Rust's async/await desugars into state machines at compile time...
No other tool comes close
HyperSearchX is the only API combining search federation, neural ranking, deep content extraction, and cross-session AI learning — features competitors don't offer at any price point.
| Feature | Best HyperSearchX | Firecrawl | SerpAPI | Perplexity | Exa |
|---|---|---|---|---|---|
Multi-source federation 11+ simultaneous backends | |||||
Token budget control (QATBE) | |||||
5-layer content extraction (CEP) | |||||
8-signal neural ranking | |||||
Evidence graphs + citations | |||||
Cross-session learning (PIE) | |||||
Deep research pipeline (AMRS) | |||||
YouTube & social search | |||||
Real-time monitoring + diffs | |||||
MCP protocol support | |||||
CLI tool included | |||||
Free tier included | |||||
Median API latency Lower is better | < 200ms | ~800ms | ~400ms | ~2000ms | ~300ms |
13 features that Firecrawl, SerpAPI, Perplexity, and Exa don't offer — even combined.
Simple, transparent pricing
Start free. Upgrade when you need more. No surprise charges, no vendor lock-in, no hidden rate limits.
Evaluation, personal projects, and exploration.
- All 11 search backends
- 5-layer CEP extraction
- HyperFusion ranking (8-signal)
- Token budget management
- Evidence graphs + citations
- Community support (Discord)
Indie developers shipping AI-powered products.
- Everything in Free
- 25,000 API requests / month
- YouTube intelligence
- Social media research
- Real-time monitoring
- Email support (48h SLA)
Teams and production AI applications.
- Everything in Starter
- 250,000 API requests / month
- PIE cross-session learning
- AMRS deep research pipeline
- Priority support (4h SLA)
- Usage analytics dashboard
Dedicated infrastructure, custom SLAs, full control.
- Everything in Pro
- Unlimited API requests
- Dedicated infrastructure
- SLA guarantees (99.9% uptime)
- SSO + team management
- Dedicated Slack channel
vs Firecrawl Pro ($599/mo): Our Pro plan ($79/mo) delivers a superset of features at 87% less cost. Federation, neural ranking, deep research, and cross-session learning that Firecrawl doesn't offer at any price.
All plans include all 17 algorithms, all 11 search backends, evidence graphs, and citations. No feature gating — only scale.