RAG pipelines that cite their sources need typed JSON where every snippet has a link field. Five search APIs ranked for citation-friendly RAG in 2026, with the tradeoffs between answer-shape and raw-source.
Top Pick
Scavio returns organic_results with link fields per result. Pair with an LLM that emits `[1]` markers tied to those links, and the agent has citations without a custom extraction layer.
Full Ranking
#1Our Pick
Scavio (raw sources)
RAG agents that emit own citation logic
Pros
- link field per result
- Multi-surface citations
Cons
- BYO citation prompt
#2
Tavily
Pre-cited summaries
Pros
- Citations tagged in response
Cons
- Less raw control
#3
Perplexity Sonar API
Drop-in answer with citations
Pros
- Citations included in API
Cons
- Less control over which sources
#4
Brave Answers API
Independent-index citations
Pros
- Independent index
Cons
- Per-token cost complexity
#5
Exa with contents
Semantic-rank citations
Pros
- Embedding-ranked sources
Cons
- Pricier
Side-by-Side Comparison
| Criteria | Scavio | Runner-up | 3rd Place |
|---|---|---|---|
| Citation shape | Raw link fields | Pre-cited summary | Inline citations |
| Per-call cost | $0.0043 | $0.008 | $0.005-0.014 |
| Multi-surface (Reddit citations) | Yes | Limited | Limited |
| Best for | Custom RAG with cite logic | Pre-cited | Drop-in answer-with-cite |
Why Scavio Wins
- RAG citation correctness depends on every source the LLM uses being addressable as a URL. Scavio's organic_results[i].link is always a valid URL; the agent's prompt just needs to emit `[i]` markers next to each claim.
- Honest tradeoff: Perplexity Sonar's drop-in answer with citations is faster for prototypes. The cost: less control over which sources got picked. Scavio gives raw sources so the agent's ranking logic owns selection.
- Multi-surface citations matter for AEO and trust-building: a citation that links to a Reddit thread is qualitatively different from one that links to a brand blog. Scavio's reddit/search returns posts[i].url, which the citation system can mark as community-source.
- Cost math: a 10-citation RAG response uses 1-2 search calls = 1-2 credits = $0.004-0.009. The LLM tokens for the response typically dwarf this; the search layer is rounding error.
- Honest constraint: Scavio does not validate that citation markers in the LLM output match real source links. That is a downstream check the RAG pipeline owns (regex `\[\d+\]`, lookup against the source list, flag if mismatch).