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Parallel Responses – Web-Grounded Cited Answer
answerssearchwebextractionresearchai
Parallel Responses – Web-Grounded Cited Answer is a paid API for AI agents from Parallel at parallelmpp.dev, paid per call via MPP, $0.01 – $0.25 depending on research effort (dynamic), status unknown (last checked 2026-10-11).
Returns a cited, web-grounded answer as JSON given a natural language question, with configurable reasoning effort.
Price / call$0.01– $0.25 depending on research effortvaries by input
Success—
StatusUnknown
How this service works
Returns a cited answer as JSON. $0.01 low / $0.05 medium / $0.25 high per request.
Output
A JSON object containing a synthesized natural language answer grounded in live web sources, accompanied by citations linking claims to their sources. The response format is flexible (additionalProperties: true) and may include the answer text, citation list, and supporting metadata depending on the query and reasoning effort level.
Example use cases
Competitive intelligence with source verification
“Get me a cited answer to 'What are Anthropic's most recently announced model capabilities and pricing as of this year?' — I need sources I can verify, use medium reasoning effort.”
Medical or regulatory fact-checking
“Find me a web-grounded, cited answer to 'What are the current CDC guidelines for RSV vaccination in adults over 60?' so I can confirm what's actually official policy right now.”
Market research with evidence
“I need a cited answer to 'Which countries have passed comprehensive AI regulation laws as of 2024, and what are their key requirements?' — use high reasoning effort so I get thorough coverage.”
Technical details
Endpoint
POSThttps://parallelmpp.dev/api/responses?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a factual, web-grounded answer with traceable citations rather than a model's parametric knowledge alone. It is ideal for research tasks where source verification matters, current-events queries where training cutoffs are a concern, and any workflow that needs to surface evidence alongside conclusions. Prefer this over the brand's Search endpoint when you want a synthesized answer rather than raw search results, and over the Task endpoint when the question is single-hop or moderate complexity rather than a long-running multi-step research task.
Side effects
- Input question is ambiguous or too vague — may return low-confidence or incomplete answer
- Web sources unavailable or paywalled — citations may be incomplete
- High reasoning effort requests may time out for extremely complex multi-hop questions
- Malformed input array (non-object items) triggers schema validation error
- Rate limiting or payment failure returns 402 or 429 error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | — | |
| reasoning | object | |
| instructions | string |
Output
Schema · Response
{
"type": "object",
"additionalProperties": true
}Tags
answerssearchwebextractionresearchai
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