Collect Video Testimonials That Build TrustBest Web Search APIs
By Venkatraman C
Last updated on Oct 5, 2026Web Search APIs allow developers to add live web search and retrieval capabilities to applications without building or maintaining a search index from scratch.
- Unified web search across multiple providers with normalized JSON responses
- Automatic provider routing and ordered provider fallback chains
- REST API and remote Model Context Protocol server access
Provider Routing and Fallbacks
OpenWebSearch separates application integration from the individual search provider. Developers can explicitly select a provider, use automatic routing, or provide an ordered fallback list. A fallback moves to the next provider when a search returns no results, times out or encounters a transient failure. The gateway returns the first successful response rather than combining results from multiple providers.
Normalized Search Interface
The REST API standardizes common search parameters and result fields across supported providers. Normalized results can contain title, URL, snippet, page content, publication date and source, while the original provider result remains accessible through raw. Provider capabilities can be inspected through GET /v1/providers, allowing applications to identify whether filters are native, emulated or unsupported.
Agent and MCP Access
OpenWebSearch exposes the search gateway as a stateless remote MCP server in addition to its REST API. The MCP endpoint provides web_search and list_providers tools and uses Streamable HTTP. MCP search results retain the normalized structure but omit the REST raw field and cap per result content to limit the amount of context passed to models.
- Multiple web search modes ranging from low latency search to deeper agentic retrieval
- Webpage content and extracted highlights designed for use as context in AI applications
- Structured outputs and AI generated summaries from web search results
Search Modes and Latency
Exa exposes multiple search modes instead of a single retrieval configuration. Its product documentation lists Instant, Fast, Auto, Deep, and Deep Reasoning Search. Fast Search is documented around 450 ms, Auto around one second, and Deep Search at approximately 4 to 12 seconds. This allows developers to select different retrieval approaches depending on the application's latency and search depth requirements.
Content and Structured Results
Search can return standard URLs and webpage contents as well as highlights that extract relevant passages from source pages. Exa also supports structured outputs for deeper searches through a supplied schema. This enables applications to request specific fields rather than processing all retrieved text independently. An AI generated summary is another available output and can be streamed.
Developer Access and Scaling
Exa documents Python and JavaScript libraries together with REST requests to the /search endpoint using Bearer authentication. Self service access includes defined Search QPS limits, while Enterprise supports custom Search QPS and up to 1,000 results per search. Exa also documents integrations with agent frameworks, model platforms, automation tools, and developer SDKs.
- AI focused web search with ranked and extracted content returned as structured results
- Configurable search depth, domain filtering, date filtering, localization, and topic controls
- Optional generated answers, raw content, images, publication dates, favicons, and usage metadata
Search and Relevance Controls
Tavily Search exposes several controls for adjusting retrieval behavior. Developers can select basic, advanced, fast, or ultra-fast search depth and configure the maximum number of results. Requests can also target general, news, or finance topics and apply time ranges, explicit start and end dates, domain restrictions, domain preferences, language settings, country boosting, exact matching, and safe search.
Content for AI Applications
The API returns more than URLs and titles. Search results contain extracted content and relevance scores, while applications can request raw content, publication dates, images, image descriptions, favicons, and generated answers. For supported search depths, developers can configure up to three short relevant content chunks per source, allowing the amount of retrieved text supplied to an AI application to be controlled.
API Access and Request Tracking
Tavily exposes the Search API at the /search endpoint using POST requests with JSON request bodies. Authentication uses a Tavily API key as a Bearer token. Tavily also supports a Project ID request header, allowing requests made with the same API key to be associated with different projects and subsequently filtered in request logs and platform usage tracking.
- Direct search access to Brave's independent web index with web, news, image, video, and other search data
- LLM Context endpoint providing extracted web content and source metadata for models and AI agents
- Search controls including freshness filtering, localization, pagination, safe search, extra snippets, and Goggles based reranking
Search Index and Result Controls
Brave Search API exposes Brave's own web index rather than acting solely as a gateway to external search providers. Web Search supports freshness filters, country and language targeting, search operators, safe search, pagination, and up to five additional snippets per result. Goggles provide another layer of control by allowing developers to boost, demote, filter, or rerank domains according to custom rules.
AI and Agent Search
Brave separates human oriented Web Search from its LLM Context endpoint, which is designed for machine consumption. LLM Context returns extracted page content grouped as grounding information together with source metadata. The Search plan includes both Web Search and LLM Context, allowing developers to choose between ranked search results and content prepared for model or agent workflows.
API Access and Versioning
The API uses REST and requires an API key in the X-Subscription-Token request header. Major API versions are included in endpoint URLs, while the optional Api-Version header can lock requests to a dated behavior version. Without this header, requests use the latest API version, giving developers a documented mechanism for managing backwards incompatible API changes.
- Unified web search across Ceramic.ai, Exa, and Linkup with normalized result formatting
- REST API and Cloudflare Workers AI binding access
- AI Gateway integration for logging, analytics, billing, access control, and provider key management
Provider Abstraction
Cloudflare Web Search API exposes Ceramic.ai, Exa, and Linkup through a common interface. Developers select the provider with one request parameter while Cloudflare normalizes responses into the same general result structure. This can simplify applications that need to change search providers because the application does not need a separate response handling implementation for each supported provider.
Request and Response Model
The REST interface uses a POST request with a required search query and request options. Developers can select a provider and specify a result limit of one to ten. Responses contain an items array and request metadata. Individual results contain URLs and titles, with descriptions and additional fields included when supplied by the provider.
AI Gateway and Authentication
Every search is routed through Cloudflare AI Gateway. REST requests use a Cloudflare API token with Workers AI Read and AI Gateway Read permissions. AI Gateway also manages search logging, analytics, provider access controls, and stored provider credentials. Developers can fund requests using AI Gateway credits or configure stored provider keys for supported search services.