Schema-shaped JSON responses
Provide a `json_format` object in the request to describe the fields your application needs. The response places the extracted result in `json_content`.
Context.dev Answers
Freemium
Context.dev Answers researches the web and returns sourced results in a JSON structure you define. It supports fast responses for shorter tasks and ultra mode for deeper research.
Context.dev Answersとは？
Context.dev Answers is a web research API for applications that need structured, source-backed information. Submit a task and define the desired JSON shape; the endpoint returns JSON content together with the sources used. Requests can use fast mode for shorter tasks or ultra mode for deeper research.
Context.dev Answersでできること
Sourced web research
Each response includes a `sources` array, allowing downstream workflows to retain the web references associated with the returned answer.
Selectable research depth
Choose `fast` for a short task or `ultra` when the request calls for deeper research, as described in the API documentation.
API-based integration
Call `POST /v1/web/answers` with bearer-token authorization and a JSON request body containing the task, mode, and requested output format.
Execution and credit metadata
Responses expose whether the result is partial and include key metadata such as credits consumed and credits remaining.
利用シーン
“Research current web facts”
Ask a defined question about public web content and return the findings in fields that can be stored, displayed, or passed to another service.
“Build structured comparison data”
Use a schema with fields such as URLs, names, or other attributes to collect comparable information across web research tasks instead of handling unstructured prose.
“Ground application workflows with sources”
Pass JSON results and their source list into an internal research, enrichment, or content workflow where traceable web evidence is useful.
よくある質問
What does Context.dev Answers return?
A successful response includes `json_content` for the requested result, a `sources` array, a `partial` indicator, and key metadata containing credit usage information.
How do I specify the output format?
Include a `json_format` object in the POST request body. The API documentation demonstrates defining fields and arrays with placeholder values to describe the desired JSON shape.
What research modes are available?
The documentation describes `fast` for short tasks and `ultra` for deeper research.
How is Answers charged?
Context.dev lists Answers from 10 credits per call in its shared API credit table. Plan allowances differ by tier; the pricing page specifically lists Fast-mode quotas for Developer, Pro, Growth, and Scale plans.
Can a result be incomplete?
Yes. The response contains a `partial` field, and the API documents timeout, rate-limit, authorization, client-error, and server-error responses. Applications should check the response status and partial indicator before using the result.
クイック情報
- Category
- Web research API
- Endpoint
- POST /v1/web/answers
- Output
- Custom JSON content with sources
- Modes
- Fast and ultra
- Authentication
- Bearer token
- Pricing basis
- From 10 credits per Answers call
Context.dev Answersの代替品
Nimble Web Search Agents
www.nimbleway.com
Nimble Web Search Agents are self-learning research agents that search and crawl the live web for domain-specific answers, enrichment, and structured datasets. They are designed for teams building repeatable research workflows where the schema, search scope, and output format need to be controlled.
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Valyu provides search, content extraction, answer, and DeepResearch APIs for AI agents and knowledge-work applications. It combines open-web results with financial, scientific, biomedical, legal, economic, and other specialist sources, returning cited content and research outputs.
Vespa.ai
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Vespa is an AI search platform for building search, retrieval-augmented generation, recommendation, personalization, and agent applications over text, vectors, tensors, and structured data. It is designed for developer teams that need configurable ranking and distributed operation at production scale.
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系統的レビューと文献レビューのためのAIプラットフォーム
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Anaraは、文献・ウェブ検索、出典付き回答、文書分析を一元化するAIリサーチワークスペースです。