Scry · Comparison
Scry, next to the search APIs
Ten products agents reach for when they need the internet, verified against their live pages with the date on every claim: the survey you would otherwise run yourself. They sell ranked results and finished answers over closed indexes. Scry sells the layer underneath: the corpus itself, open to SQL.
The market, one row per product
| Product | Class | A call returns | Index & corpus | Result depth & limits | Price | Latency | MCP | Status / SLA | Backing | Verified |
|---|---|---|---|---|---|---|---|---|---|---|
| Exa | ranked web search | ranked links + extracted content | own neural index (transformer embeddings, own GPU fleet); claims 500B URLs tracked, hourly updates; no document count published | 10 included; each further result billed | $7 /1k searches + $1 /1k extra results; contents $1 /1k pages; deep tiers $12–15 /1k | claims ~250 ms (instant tier) to ~40 s (deep-reasoning) | yes | status page 99.97%; no SLA published | $335M+ raised; $2.2B valuation (May 2026) | 2026-09-03 |
| Brave Search API | ranked web search | ranked links, news, images; answers tier | own index: claims 30B+ pages, 100M+ updates/day, fed partly by opt-in browser Web Discovery data | top-k pages per call, 50 qps | $5 /1k requests; answers $4 /1k + $5 /1M tokens | SOC 2 Type II; no SLA % published | Brave Software (browser-scale org) | 2026-09-03 | ||
| Tavily | ranked web search | ≤20 results as ≤500-char snippets; optional answer | hybrid: own crawler (presents as Googlebot-compatible) + per-query aggregation of third-party search data; no size published | 20 results, 500-char chunks — hard shape | $0.008 /credit; search 1–2 credits; plans from $30/mo (4k credits); free 1k/mo | claims 180 ms p50 | yes | claims 99.99% SLA; public status page | $25M raised (Series A, Aug 2025) | 2026-09-03 |
| Parallel | ranked web search | ranked results; task tier returns finished research jobs | own crawl + index; no size published; vendor-run benchmark tables at parallel.ai/benchmarks | 10 results per search request | search $1–5 /1k; extract $1 /1k results; task processors $5–2,400 /1k; free 5k/mo | yes | SOC 2; enterprise ZDR | founded by Parag Agrawal (ex-Twitter CEO) | 2026-09-03 | |
| Linkup | ranked web search | cited answers + full-text snippets | aggregated web retrieval; sources and freshness tunable per call; index provenance unpublished | answer + snippets per call | search $5–6 /1k; fetch $1–6 /1k; research runs $0.25–2.50 each; free 4k queries | claims 1–3 s sync search, <2 s fetch | SOC 2 Type II on all plans | clients incl. McKinsey, Databricks, Cohere | 2026-09-03 | |
| Perplexity Sonar | answers & reports | prose answer + citations; raw search endpoint | own crawler + index built for the consumer answer engine | one answer per call | search $5 /1k; Sonar $1/$1 per 1M tokens + $5–12 /1k requests; Pro $3/$15 + $6–14; deep research token-billed + $5 /1k searches | Perplexity (consumer-scale org) | 2026-09-03 | |||
| Elicit | answers & reports | papers, screening tables, extraction columns, reports | 138M papers + 545k trials — Semantic Scholar, PubMed, OpenAlex merged; the moat is the workflow, not the retrieval | 300 results/request (Pro) to 10,000 (Enterprise); 100 req/min per IP on every plan | API from the $49/mo Pro plan; Scale $169/mo; Enterprise custom | yes (OAuth) | ~$31M raised; ~57 people (trackers); PBC | 2026-09-03 | ||
| Consensus | answers & reports | top-20 papers with extracted study-design metadata | scientific papers; provenance not detailed publicly | 20 results per call — the whole surface | from $0.10 /call + platform fee; application-gated, custom quotes | no | 2026-09-03 | |||
| Semantic Scholar | open scholarly data | scholarly metadata records; citation graph | 214M papers, 2.49B citations, 79M authors | paginated; 1 request/sec keyed | free | best-effort (rate-limited for politeness) | Ai2 (Allen Institute for AI) | 2026-09-03 | ||
| OpenAlex | open scholarly data | scholarly metadata records; group-by aggregations | 323.5M works (live API count on the verified date), CC0 | paginated; full snapshot downloadable | free; paid premium for faster update feeds | best-effort | OurResearch (open infrastructure) | 2026-09-03 | ||
| Scry | programmatic search | the rows you asked for — or the answer computed from all of them | own archive of the public internet as one corpus; coverage published as measured dents (26.9B Reddit comments = 94% of all ever written) | no page 2 — your LIMIT; aggregations read every matching row (a published study read 50.46B rows in 15 m 46 s) | free under slack; congestion reprices; each response reports its cost | engine-reported per query; a 111-iteration recursive loop returns in ~50 ms | yes | private alpha, own hardware | ExoPriors | 2026-09-03 |
Latency, index-size, and SLA figures are each vendor’s own published claims. A blank cell means the fact could not be verified either way.
Capabilities
| Capability | Scry | Exa | Brave | Tavily | Parallel | Linkup | Sonar | Elicit | Consensus | S2 | OpenAlex |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Live-web retrieval on demand | — | ● | ● | ● | ● | ● | ● | — | — | — | — |
| Archive depth (years of record, stable refs) | ● | — | — | — | — | — | — | ◐ | ◐ | ● | ● |
| Full-text content extraction | ● | ● | ◐ | ● | ● | ● | — | ◐ | — | — | — |
| SQL: aggregation, joins, GROUP BY | ● | — | — | — | — | — | — | — | — | — | ◐ |
| Recursion & graph programs | ● | — | — | — | — | — | — | — | — | — | — |
| Computation without a result cap | ● | — | — | — | — | — | — | — | — | — | — |
| Corpus enumerable & auditable | ● | — | — | — | — | — | — | — | — | ● | ● |
| Per-row provenance fields | ● | ◐ | ◐ | ◐ | ◐ | ◐ | ◐ | ◐ | ◐ | ● | ● |
| Bulk snapshot export | — | — | — | — | — | — | — | — | — | ● | ● |
| Synthesis reports / review workflow | — | ◐ | — | ◐ | ◐ | ◐ | ● | ● | ◐ | — | — |
| MCP server | ● | ● | ● | ● | ● | — |
● yes ◐ partial — no blank: not verified.
Which one, when
| The ten best links from the live web, in under a second | Exa or Brave |
| One cited answer with no agent scaffolding | Perplexity Sonar |
| Drop-in web tool call for a LangChain-era agent framework | Tavily |
| A whole research task as one metered request | Parallel (task tier) |
| A systematic review: screening, extraction, PRISMA-shaped output | Elicit |
| Scholarly metadata in bulk, free, no strings | OpenAlex or Semantic Scholar |
| Count, join, rank, sweep, or walk the whole record — not the top ten | Scry |
Where each wins, where each stops
| Product | Wins | Stops |
|---|---|---|
| Exa | strongest semantic top-k over the live web; richest latency ladder; heaviest-funded pure search API | ranked lists only; index unauditable; results past ten billed per item |
| Brave Search API | largest independent index for rent; cleanest per-query price in the ranked class | top-k pages; the index cannot be queried as data |
| Tavily | broadest agent-framework integrations; snippets pre-cut to context windows | 20 results × 500 chars is the product’s hard shape |
| Parallel | lowest price floor ($1 /1k); task tier runs whole jobs per request | ranked results and finished outputs; no computation over the index |
| Linkup | cited-answer ergonomics; per-call source control; low price | retrieval underneath is a black box you steer but cannot inspect |
| Perplexity Sonar | one call replaces a search-read-synthesize loop | prose and citations only, never the corpus; costs compound on tokens and requests at once |
| Elicit | real systematic-review machinery no raw corpus provides | scholarly records only; hard caps; per-IP limit that paying more (below Enterprise) does not lift |
| Consensus | clean extracted study-design metadata per paper | twenty results per call is the entire programmatic surface |
| Semantic Scholar | free citation-graph truth; bulk downloads | metadata only; 1 req/sec; all computation happens on your machine |
| OpenAlex | the whole catalog, downloadable, CC0 — Scry serves OpenAlex-derived relations itself | server-side power ends at filtered listing and group-by |
The Scry row, expanded
| Query surface | read-only SQL (ClickHouse dialect) + WITH RECURSIVE + fixpoint graph programs; vector helpers; rerank |
| Corpus | the public internet as one corpus: forums, scholarly literature, prediction markets, social archives, newsletters, public records — billions of new posts and comments daily |
| Depth | no page 2; answers computed over every matching row (published study: 50.46B rows in 15 m 46 s) |
| Coverage honesty | published as measured dents — 26.9B Reddit comments, 94% of all ever written, the miss computed by exact subtraction |
| Transparency | live schema is the contract; every response returns the executed SQL and engine accounting |
| Provenance | source, batch, and timestamp fields on every row |
| Connect | one MCP URL (mcp.scry.io) for Claude Code, Codex, ChatGPT, Cursor; HTTP API with the same key |
| Price | free under slack; under measured congestion, admission reprices; each response reports its cost |
| Docs | turing-complete search and the calculus it implements, at /docs |
Sources for the Scry figures: studies carry the engine-reported timings, and the docs carry the query calculus. The asymmetry the whole page reduces to: a ranked list can always be built on top of a corpus, but a corpus cannot be recovered from ten links.
What they do better, today
Ranked one-shot answering over the live web is their whole product, and the leaders are excellent at it: when your agent needs the ten best links or one cited answer in two seconds, use them. Their extract and crawl endpoints reach arbitrary URLs the moment you ask. Elicit’s screening and extraction tables are years of dedicated workflow product. And they carry the operational trappings of bigger teams: SOC 2 attestations, public status pages, enterprise SLAs. Scry is a private alpha on its own hardware, and this page will keep saying so for exactly as long as it stays true.
FAQ
- Which of these should my agent actually use?
- For ten good links or a one-shot cited answer over the live web in a couple of seconds, use a ranked search API — Exa and Brave are the strongest for retrieval, Sonar for finished answers. For a systematic literature review with screening and extraction, Elicit sells exactly that workflow. When the question is computational — count, join, rank, sweep, walk a graph, check every row rather than the top ten — that is the layer Scry serves.
- Is Scry a web search API?
- Scry serves search and fetch tools over its own archive of the public internet, so MCP clients can use it like one. The difference is what sits underneath: the same corpus answers arbitrary read-only SQL, so retrieval is one query shape among many rather than the whole product.
- Why does the Scry row show no result cap?
- Because the unit is the query, not the result list. A statement carries its own LIMIT, and aggregations return computed answers over every matching row. One published study read 50.46 billion rows in under 16 minutes.
- What do these products do better than Scry?
- Ranked one-shot answering over the live web — that is their entire product, and they are excellent at it. Fetching an arbitrary URL this second. Elicit’s screening and extraction workflow. And operational maturity: larger teams, SOC 2 attestations, public status pages with long uptime histories. Scry is a private alpha run on its own hardware.
- How current is this page?
- Every row carries the date its facts were verified against the vendor’s live pages, and prices are quoted from those pages, not from memory. A blank cell means we could not verify the fact either way. When a number drifts, write [email protected] and we will re-verify.