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AgentRAG – Hybrid Retrieval-Augmented Query
x402
AgentRAG – Hybrid Retrieval-Augmented Query is a paid API for AI agents from api.agentx402.ai, paid per call via x402, $0.008/call, status unknown (last checked 2026-09-15).
Accepts a natural language query and optional source URLs, performs hybrid dense-vector + BM25 retrieval with reranking, and returns ranked, cited text chunks relevant to the query
Price / call$0.008
Success—
StatusUnknown
How this service works
Agent-native retrieval over x402 — send a query and, optionally, source URLs to index: get back ranked, cited chunks. Hybrid retrieval by default (dense vectors + BM25 keyword search, fused and reranked) beats vector-only search on exact tokens (error codes, API symbols, config keys). Pay-on-success: a query that matches nothing settles nothing. Ask $0.008; prepay $1 = 10,000 credits, spent at 80% of the per-op price (20% off). Docs: https://agentx402.ai
Output
A list of ranked, cited text chunks matching the query, each accompanied by its source URL and relevance score, produced via fused dense-vector and BM25 retrieval with reranking. If no chunks match the query, no payment is settled.
Example use cases
API error code lookup in docs
“Search through the indexed API documentation at https://docs.stripe.com for everything about error code 'card_declined' — give me the top ranked cited passages explaining causes and remediation.”
Config key discovery for DevOps
“Look up the config key 'MAX_RETRY_INTERVAL' in my indexed infrastructure docs at https://internal.docs.myco.com and return the most relevant chunks explaining what it controls and its valid values.”
Research synthesis from multiple sources
“Query these three URLs — https://openai.com/docs, https://anthropic.com/docs, https://cohere.com/docs — for how each handles context window limits, and give me ranked cited excerpts from each.”
Technical details
Endpoint
POSThttps://api.agentx402.ai/v1/rag/askWhen to prefer
Prefer AgentRAG when you need precise retrieval over exact tokens such as error codes, API symbols, or configuration keys, where vector-only search underperforms. It is ideal when you have specific source URLs to ground retrieval and want cited, ranked chunks rather than a generated answer. Choose it over general web search when you want retrieval scoped to known documents, and over a pure vector store when keyword matching matters alongside semantic similarity.
Side effects
- Query matches no indexed content — returns empty results and no payment is charged
- Provided source URL is unreachable or returns non-indexable content — indexing skipped for that source
- Malformed query or missing required 'input' field — returns 400 validation error
- Rate limit or credit exhaustion — returns 402 payment required or credit insufficient error
- Source document too large or unsupported format — partial indexing or rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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