A team building an AI assistant needs a different search API than a team tracking Google rankings. Developers and technical buyers face a practical choice: get useful web results without adding tools their workload does not need.
The best api search company’s homepage can help you start a commercial evaluation, but a polished front page does not prove technical fit. Providers return different outputs and charge by different measures. “Best” means the right fit for your use cases, not a universal winner.
This guide compares options for SERP data, AI grounding, semantic discovery, and page extraction. Before comparing providers, decide whether your application needs links, extracted page content, or complete structured records.
Key Takeaways
- Choose the API category by the data your application needs.
- Test real queries before you commit to an integration.
- Compare billing units, not just headline prices.
- Check response formats, speed, and request limits.
- Keep credentials and sensitive data out of unsafe places.
What Kind of Search API Fits Your Application?
A rank-tracking dashboard needs SERP data, while a chatbot usually needs source passages or page text. A web search API returns machine-readable results through programmatic requests. A SERP API retrieves structured search engine results page data, such as result links, snippets, and other SERP features.
Choose by the output your system must store or show. Search APIs can return snippets, passages, page text, or structured data, and those formats support different tasks.
Match the API category to the output your application must store or show, not just the provider’s search box.
SERP data, AI retrieval, and site search
A SERP API is built for rankings, result links, snippets, and features such as news or image results. It helps you track search visibility or find URLs for later processing.
An AI-native retrieval API finds pages or passages that can ground a large language model, or LLM. Its results may emphasize meaning and source context instead of matching a search engine’s rank order.
A site-search API searches a company’s own content. Algolia, Elastic, and Google Programmable Search are examples. Google Programmable Search targets a company’s own domain, so it does not replace every open-web API.
Crawling and extraction from known pages
A scraping API extracts content from URLs you already know or select. It can return page text or structured records for use in another system.
That makes extraction useful when you have a set of pages to monitor, while web search helps you discover pages across the web. The distinction matters: an API that finds a link may not fetch its full content.
For example, a support chatbot might need passages from approved help pages, while a monitoring tool may need fresh page text. Match the API category to the output your application must store or show, not just the provider’s search box.
How to Evaluate the Best API Search Company’s Homepage
A useful provider homepage lets you verify the product’s output and try a first request without a sales call. The best api search company’s homepage makes the product and its developer path easy to assess.
Look for five practical checks before you plan an integration. A clear use case and response example help you see whether the platform fits your task.
Check the technical information first
Start with the endpoint and response format. You should be able to tell whether the API returns ranked links, passages, extracted text, or another form of data.
Then check whether the company explains authentication, request limits, and error responses. Performance details and security information help your team estimate the work beyond a basic test call.
Stripe and Twilio are familiar examples of developer products with clear documentation and practical integration guidance. They are examples of developer-resource presentation, not search API recommendations.
Look for a low-friction developer path
A short checklist can keep a homepage review focused:
- Clear use case and output format
- Reachable documentation with request examples
- Working playground or demo
- Readable pricing and billing units
- Links to security and service-status information
A usable demo can expose gaps that marketing copy hides. Try a small request and inspect the response before you compare platforms or estimate integration time.
Polished claims without an endpoint example or usable docs are a warning sign. Treat a missing documentation link or an unclear response example as a reason to test more carefully before committing.
Which Search APIs Belong on Your Shortlist?
A useful shortlist starts with the response your application needs, not the provider with the most features. These five search API options serve different use cases and return different kinds of results.
These are product categories, not interchangeable score rankings. Compare what each API returns with the content and data your downstream system expects.
| Provider | Search approach | What the response emphasizes | Best-fit task |
|---|---|---|---|
| Brave Search API | Independent index | Ranked web results | General web search |
| Firecrawl | Search plus optional fetch | Passages or full page | Agent workflows needing extraction |
| Exa | Neural retrieval | Semantically relevant pages | Research discovery |
| Tavily | LLM-oriented search | Source-focused results | RAG and question answering |
| SerpAPI | SERP retrieval | Metadata and search features | SEO and multi-engine monitoring |
Brave centers on web results from its own index. Firecrawl can add page fetching to a search workflow, while Exa focuses on semantic discovery.
Tavily shapes its search tools for LLM workflows and source-focused answers. SerpAPI is a better match when your system needs search engine metadata, rather than fetched page content.
Remove any option that cannot return the data format your downstream system can reliably process. That simple filter can spare your team from building extra conversion code around the wrong response.
Which Search API Works Best for AI Agents and LLMs?
For a general-purpose AI agent that needs current web results, start by testing Brave Search API, then compare whether Firecrawl’s optional page fetch or a specialist retrieval API better fits the workflow.
Match the result format to what your model will read. A link list may require another fetch step, while ranked passages can provide source context sooner.
Grounding an answer with current sources
Brave is a fast general web-search choice to test when an agent needs current results. Firecrawl can return ranked, LLM-ready passages and optionally fetch a full page in the same call.
Exa suits semantic discovery when the user’s wording differs from the wording on relevant pages. Tavily offers search, extract, crawl, map, and research endpoints for source-focused RAG, or retrieval-augmented generation.
A free web search tool for an LLM should be judged by result quality, source links, and usable content. Access without a card can help you test, but it does not show whether results suit your model or task.
For a broader view of assistant choices, compare AI chatbots for research and other workflows. The right assistant still depends on the tasks and apps your team uses.
Getting page content without a separate workflow
An agent may need to read more than a title and snippet. When the model needs full page text, test whether the search API can fetch it or whether your system needs a separate extraction step.
Keep source URLs in the model’s input so you can trace the answer back to its evidence. Then check whether the returned passages retain enough context for the model to use them correctly.
Run a small set of representative prompts through the exact response format your model will consume. Include questions that need recent facts and questions that need deeper page content.
When Should You Choose Brave Search API?
Brave is a strong first test when you want web results from an index that does not hand off to Google or Bing. Its search API and LLM Context endpoint serve different needs.
Estimate throughput from the endpoint you plan to call. In 2026, web search costs $5.00 per 1,000 requests and supports 50 requests per second.
Web results and LLM Context
Brave Search API uses its own index. Standard web search returns ranked links and related search data, while LLM Context returns machine-oriented passages with source URLs and timestamps.
In 2026, LLM Context supports a token setting from 1,000 to about 33,000 tokens. You can choose strict, balanced, or lenient relevance thresholds and filter for results from the last 24 hours.
The LLM Context endpoint supports 2 requests per second, which can constrain parallel workloads. Its rate is much lower than standard web search, so a high-volume agent may need a queue.
In 2026, Brave web search costs $5.00 per 1,000 requests. Brave also includes $5 in free credits each month, applied to the account.
Spellcheck, autosuggest, and OpenClaw settings
Spellcheck and autosuggest each cost $5.00 per 10,000 requests and support 100 requests per second in 2026. They can help search interfaces handle typos and incomplete queries.
OpenClaw’s Brave provider accepts the BRAVE_API_KEY environment variable. It supports country, language, and time filters in 2026.
- Set BRAVE_API_KEY in your environment.
- Choose a country and language when your query needs them.
- Use a time filter when results must be fresh.
Estimate concurrency from the endpoint you will call, since the LLM Context limit is much lower than the search endpoint’s. A test at low volume may not reveal a queueing problem.
Is DuckDuckGo a Free Search API?
DuckDuckGo offers a free, no-key Instant Answer API, but it is not a full web search results API. It returns structured answers, abstracts, and related topics.
Use it for lightweight answer data, not exhaustive web discovery. Its response can include an Abstract, AbstractText, AbstractURL, RelatedTopics, Answer, and Type.
The Instant Answer API can support a tool that needs a short fact or related topic. It does not provide the full ranked result set you would expect from a general search API.
In 2026, the Python package ddgs is unofficial and retrieves results through HTML endpoints, rather than an official search API. OpenClaw’s DuckDuckGo integration also uses an unofficial HTML-based method and needs no API key.
Those tools may help with a quick prototype, but HTML-based integrations can be less stable than an API with a supported contract. Changes to a page can break a tool that relies on its markup.
Check that the response fields fit your application before you build around them. Use the Instant Answer API only when abstracts and related topics satisfy the job, and test unofficial HTML integrations before relying on them in production.
Which Free Web Search APIs Work With OpenClaw?
For a free web search API for OpenClaw, DuckDuckGo needs no API key, while other providers offer different trial or credit arrangements.
A free tier helps only when it covers your test workload and works with your agent. In 2026, OpenClaw supports providers such as Brave, DuckDuckGo, Exa, Firecrawl, and Tavily.
Free access for testing LLM workflows
Tavily and Exa each include 1,000 free searches per month in 2026. Firecrawl keyless search works without signup, an API key, or a credit card, with rate limits per IP.
Brave offers free credits under its own terms, while DuckDuckGo’s OpenClaw integration needs no key. These options do not provide identical access or response formats.
A free web search API for an LLM is useful only if its results meet your needs. Test source links and content quality, not just whether a request succeeds without payment details.
OpenClaw supports other providers in 2026, including Gemini, Grok, Kimi, MiniMax Search, Ollama Web Search, Parallel, Perplexity, and SearXNG. Your choice depends on the agent setup and the response type you want.
Configure providers and verify tool availability
Configure the provider in Settings → Search or run openclaw configure –section web. Then confirm that the agent can call the search tool.
- Choose and configure a provider in Settings → Search or with the CLI.
- Run a test request using a query your agent should handle.
- Confirm that web_search appears in the agent’s tools.
OpenClaw caches web_search results by query for 15 minutes by default, and you can change that duration. Structured providers normalize results into a shared results shape, while synthesized providers return an answer shape.
Without a managed provider or model-native search, web_search is omitted from the agent’s tool list in 2026. If web_search is absent from the tool list, check for a managed provider configuration or native model search before debugging the query.
How Do Exa and Tavily Compare for Semantic and Research Search?
Exa is the stronger pick for the listed people, company, and publication-retrieval benchmarks, while Tavily remains an option for source-focused RAG workflows.
These tests show stronger Exa results on specific retrieval tasks, not a guarantee for every query. The table gives rank-one recall, or how often the right result ranked first.
Recall on people, company, and publication queries
| Retrieval task | Exa rank-one recall | Tavily rank-one recall | Query count |
|---|---|---|---|
| People search | 75.5% | 40.5% | 200 per provider |
| Company search | 81.5% | 61.3% | 200 per provider |
| LitSearch publication retrieval | 63.3% | 31.8% | 597 queries |
In 2026, Exa recorded higher rank-one recall than Tavily on all three listed tasks. Your own topic, query wording, and desired sources may produce a different result.
For more on research tools and model choices, see alternatives for research-focused workflows. Check citations against the pages they name, since a citation alone does not prove accuracy.
Index depth, filters, and search speed
Exa said its index tracked over 2 trillion URLs and served 100 billion pages in 2026. Its academic index held more than 350 million works, while its people and company indexes included over 1 billion profiles.
Those profile indexes had more than 50 million weekly updates in 2026. Exa’s includeDomains and excludeDomains filters each support up to 1,200 entries.
Exa offers lite, auto, and deep search types, with processing times from about 450 milliseconds to about 15 seconds in 2026. Pick the type that fits the depth and response time your task can accept.
Tavily charges one credit for basic search and two for advanced search. Its published standard-tier limit is 1,000 requests per minute in 2026.
Test both APIs on your own query set if your subjects fall outside people, company, or publication discovery. Include queries that reflect the names, fields, and source types your users actually need.
When Does Firecrawl Make More Sense Than a Basic SERP API?
Firecrawl is a better fit than a basic SERP API when the next step is to read or extract content from discovered pages.
Search plus optional page fetching can keep an agent’s workflow in one place. A SERP API may return metadata only, leaving page retrieval to another service.
Search and extraction in one workflow
Firecrawl Search can return ranked passages and optionally fetch a full page in the same call. This suits an agent that needs to find a page, read it, and pass useful content to a model.
In 2026, its free tier provides 1,000 credits per month, and search costs 2 credits per 10 results. Keyless search can run without signup, an API key, or a credit card, but it is rate-limited per IP.
That keyless mode gives you a way to test basic queries before creating an account. It is useful for a small evaluation, not a promise of unrestricted production access.
Specialized indexes and provider tools
Firecrawl’s Developer Index covers more than 70 million READMEs, GitHub issues, pull requests, and documentation, refreshed daily in 2026. It can help with coding questions that need developer content.
Its Research Index covers more than 3 million arXiv papers. The Life Sciences category extends coverage to more than 41 million drug-discovery, clinical, and biology papers in 2026.
Firecrawl Alexandria offers more than 90 data providers and three indexes. Tool discovery is free, while tool execution is billed at its listed price.
Try the keyless endpoint with a small, representative query set before designing a production workflow around it. Check whether the returned passages and fetched page content give your agent enough context.
Which SERP API Fits SEO and Google Search Work?
Choose a SERP API when you need ranked search results or SERP features, not full page text. It fits rank tracking, result-feature analysis, and URL discovery.
Use SERP data when your pipeline handles page fetching separately. The API returns search metadata your system can track, compare, or pass to another step.
Multi-engine results and SERP features
SerpAPI returns structured SERP metadata from Google, Bing, DuckDuckGo, Yahoo, Amazon, eBay, Walmart, and YouTube. That range can suit market monitoring across search engines and marketplaces.
Its response focuses on result details and search features, rather than full page content. Your tracking system can store rank, links, and supported SERP data, then fetch pages separately when needed.
Google-focused results and budget alternatives
Zenserp returns Google web, image, news, and shopping results as structured JSON. It supports localization and language parameters for reports focused on a target market.
Google Programmable Search is for searching a company’s own domain, not for general SERP collection. SerpAPI’s free tier includes 250 searches per month in 2026, which is a limited evaluation allowance.
Confirm that the engine, country, language, and result features your report needs are supported before connecting a rank tracker. A mismatch can leave gaps in a report even when requests succeed.
When Should You Use Scraping and Extraction Platforms?
Use a scraping or extraction platform when you already know which pages or sources must be collected. Search APIs find pages, while extraction tools gather content from known or selected sources.
Choose the tool by whether you need page text, custom collection logic, or entity records. These tasks often need different methods and output formats.
Known-URL crawling collects content from pages you specify. Source-specific extraction applies custom rules to a site or set of sites, while entity extraction turns content into records about people, companies, products, or articles.
Firecrawl converts websites into Markdown, JSON, or HTML. Diffbot extracts company, person, product, and article entities as structured JSON.
Apify provides customizable extraction actors, scheduling, and proxy rotation. Its marketplace includes actors for Google Search, Amazon, LinkedIn, and social platforms.
- Use an extraction platform for a known source list and custom collection logic.
- Use a structured extraction service when you need entity records.
- Use a search API when discovery across the web comes first.
Scraping is not a shortcut when your real need is ranked results from an established search engine. Separate discovery from extraction in your design if each needs different filters, schedules, or data validation.
How Should You Compare Latency and Request Limits?
In the reported 2026 comparison, Brave had the lowest average latency among the seven listed providers at 669 milliseconds.
Use latency as a comparison point, not a promise about your production response time. Query type, region, and request load can change what your system sees.
Compare response times under the same conditions
| Provider | Average latency | Test value |
|---|---|---|
| Brave | 669 ms | 2026 comparison |
| Tavily | 998 ms | 2026 comparison |
| Exa | 1,200 ms | 2026 comparison |
| Firecrawl | 1,335 ms | 2026 comparison |
| SerpAPI | 2,400 ms | 2026 comparison |
In the same test, Perplexity measured 11,000 milliseconds and Parallel Pro measured 13,600 milliseconds. Those averages describe that test, not every request your users will send.
Compare APIs with the same query mix, region, and concurrency as your production workload. A test of simple queries may not represent research calls or requests that fetch full pages.
Check throughput and plan for rate limits
Latency measures how long a response takes. Capacity limits measure how many requests an endpoint can handle over time, so the two figures answer different questions.
A fast endpoint can still reject bursts that exceed its request limit. A high-capacity endpoint can still feel slow when its responses take longer to arrive.
Benchmark with your own query set and concurrency before setting a user-facing timeout. Include the slowest calls your application can reasonably make.
What Security and Integration Checks Matter Before You Sign Up?
A successful test call does not prove that an API is safe or resilient enough for production. Check how your team will protect credentials and handle failures.
Keep API keys out of source code and client-side apps. A leaked key can let others use your account or run up requests.
Protect credentials and review data handling
Use a short checklist before sending real data:
- Store API keys outside source code.
- Review data retention and model-training terms.
- Test authentication and error responses.
- Confirm SDK or plain HTTP support.
Check the provider’s terms before sending prompts, records, or other sensitive content. Your team should know how long the provider keeps data and how it may use it.
Confirm the integration path and failure behavior
Test both valid and invalid credentials, along with timeouts and failed requests. Your application needs a clear path for errors, not just a working response.
HTTP 429 means Too Many Requests. Your client should use planned retries and backoff, rather than sending a tight loop of repeat requests.
OAuth 2.0 is a standard authorization framework, and OWASP publishes the API Security Top 10. Your team can use these terms to guide a review without assuming a provider has a certification.
Keep credentials out of client-side code and verify the provider’s retention terms before sending sensitive prompts or records. Make those checks part of your integration review, not an afterthought.
How Much Does a Search API Cost at Your Expected Volume?
Compare the unit that triggers billing before deciding which published rate is cheapest. A search, a request, a result batch, and a token may count differently.
The billing unit can change the cost of a useful result. Read the rate with its credit rules and response type, not as a stand-alone number.
Compare the billing unit, not just the headline rate
| Provider | Billing unit | Published rate | Cost detail |
|---|---|---|---|
| Brave Search API | Per 1,000 requests | $5.00 | Separate token-based LLM Context meter |
| Exa | Per 1,000 searches | $1.50 | 1,000 free searches monthly |
| Tavily | Per 1,000 basic searches | $8.00 | Basic and advanced searches use different credits |
| SerpAPI | Per 5,000 searches | $75 starting plan | 250 free searches monthly |
| Serper | Per 1,000 searches | $0.30-$1.00 | Google SERP access |
Estimate costs using your real request mix
Brave LLM Context costs $4.00 per 1,000 queries, plus $5.00 per million input tokens and $5.00 per million output tokens in 2026. Token use adds a separate charge to the query rate.
ScrapingDog costs $0.29-$1.00 per 1,000 searches in 2026. Its rate and Serper’s rate look low, but your workflow may need other paid steps.
Credits, token use, extraction, and search depth can change the effective cost per useful result. A request that returns page content may serve a different role than one that only finds a link.
Estimate spend from the calls, results, and extraction steps your actual workflow will run. Do not compare unlike billing units as if they were the same service.
Estimate spend from the number of calls, results, and extraction steps your actual workflow will run. Include the mix of basic and advanced queries your application is likely to send.
Conclusion
The best provider is the one that returns the right evidence in a format your system can use at a cost you can forecast. Start by matching the response type to your application.
Then compare providers with the same real queries and billing units. Track relevance, latency, and the cleanup your system needs before it can use each response.
Run a small pilot on your own workload, then expand only after the results and usage charges meet your requirements.
FAQ
Is Brave Search API free to use?
Brave Search API includes $5 in free credits each month, and web search costs $5.00 per 1,000 requests. The monthly credit covers some usage; it does not change the published rate. Brave applies the credit to the account automatically. Your actual bill depends on the number and type of requests that use the API.
How do I connect Brave Search to OpenClaw?
Set the BRAVE_API_KEY environment variable, then configure web search in OpenClaw. You can use Settings → Search or run openclaw configure –section web. After setup, test a query and confirm that web_search appears among the agent’s tools. If the tool does not appear, check the provider configuration or native model search setting.
Can DuckDuckGo’s Instant Answer API return full web search results?
No, DuckDuckGo’s Instant Answer API returns structured answers, abstracts, and related topics rather than full web search results. Its fields can include an answer, abstract text, a URL, and related topics. That can work for a lightweight answer feature, but it does not provide a complete ranked result list for broad web discovery.
How many requests per minute does Tavily allow?
Tavily’s published standard-tier limit is 1,000 requests per minute. Basic searches use one credit, while advanced searches use two credits. The request limit and credit use measure different things: one sets the rate of calls, and the other affects how quickly your plan’s search credits are used.
What is the difference between a SERP API and a scraping API?
A SERP API returns ranked result metadata, such as links, snippets, and search features. A scraping API extracts content from known URLs or selected pages. You might use a SERP API to find pages for a rank report, then use a scraping API when your system needs page text or structured content.
Can a search API return page text as well as links?
Yes, some search APIs return page text or passages as well as links. Firecrawl can return ranked passages and optionally fetch a full page in the same call. A SERP API may return metadata only, so check the response format before you build a workflow that expects full content.
