AI agent grounding
Give an agent current web results or pre-extracted context before it generates an answer.
Independent tool overview
Brave Search API gives developers web results, AI-ready context, and cited answers from Brave's independent search index.
Visit the official Brave Search API site ↗
Overview
Brave Search API is a developer service for adding live web search to agents, chatbots, research tools, and conventional search experiences. It uses Brave's own web index instead of repackaging results from Google or Bing.
The product spans raw search results, content prepared for language models, and generated answers. Teams can choose whether they want links and metadata for their own ranking pipeline, compact context for retrieval-augmented generation, or a streamed answer with citations.
The main implementation decision is not simply which endpoint to call. Developers should also test result quality on their own query set, control source selection, preserve citations, handle rate limits, and confirm that their plan permits any intended result storage or model-training use.
Use cases
The strongest fit depends on the job you need the product to complete, not the size of its feature list.
Give an agent current web results or pre-extracted context before it generates an answer.
Build web, news, image, video, local, and other search experiences without maintaining a crawler and index.
Return generated answers with verifiable web citations through an OpenAI-compatible endpoint.
Collect current sources for market intelligence, company research, reputation tracking, or content discovery.
Capabilities
Returns results from Brave's own global search index rather than scraping another major search engine.
Provides ranked URLs, snippets, news, images, and metadata, with options such as freshness, country, language, and safe-search controls.
Extracts and ranks compact text, tables, code, and other page chunks for agents and retrieval-augmented generation.
Generates web-grounded answers with citations, streaming, optional multi-search research, and OpenAI SDK compatibility.
Supports endpoints for images, video, news, suggestions, spellcheck, places, and other search-specific needs.
Lets Search-plan customers rerank or filter results and receive additional snippets and structured metadata.
Process
Step 1
Use Search for ranked results, LLM Context for model-ready evidence, or Answers for a completed cited response.
Step 2
Subscribe in the API dashboard, send the subscription token from a server, and keep it out of browser code and public repositories.
Step 3
Set locale, freshness, safe-search, result count, and endpoint-specific options for the product's audience.
Step 4
Test relevance on representative queries, display source links, track rate-limit headers, retry carefully, and monitor cost per successful task.
Cost
Public plans are usage based and include $5 in credits each month. Search is billed per request; Answers adds token charges. Custom enterprise terms are available.
$5 per 1,000 requests
Search results and AI-ready context from Brave's index.
$4 per 1,000 requests + $5 per million tokens
Generated, cited answers grounded in one or multiple searches.
Custom pricing
For custom capacity, terms, support, or endpoints.
Pricing checked . Check current pricing at the source ↗
Assessment
Compare
The right alternative depends on the specific output, workflow, controls and budget your project requires.
Data Analysis
Choose Exa for semantic web discovery, content retrieval, and research workflows designed specifically around AI applications.
Explore Exa →Agents
Choose Parallel Search for an agent-focused search API with a different retrieval and pricing model.
Explore Parallel Search →Data Analysis
Choose Perplexity when you want a finished consumer research experience instead of building directly on a search API.
Explore Perplexity →Questions
The public Search and Answers plans include $5 in credits each month. Brave says a payment card is required as an anti-fraud measure.
No. Brave says the API is powered by its own independent web index rather than scraping and repackaging Google or Bing results.
Search returns ranked results and metadata. LLM Context returns extracted chunks optimized for a model. Answers generates a cited response and can perform one or multiple searches.
Not automatically under every plan. Brave says storing results in part or whole requires a plan that explicitly grants storage rights.
Yes. The LLM Context endpoint is specifically designed to supply compact, relevant web evidence to agents and retrieval-augmented generation pipelines.
Build a fixed set of representative queries, judge relevance and freshness, measure latency and cost, inspect citations, and compare failure cases against other providers before committing.
Bottom line
Brave Search API is a compelling foundation for teams that want current web data from an independent index and the flexibility to choose results, extracted context, or completed answers. Its value should be proven with workload-specific relevance tests and a careful review of storage rights and production rate limits.
Visit Brave Search API website ↗
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