2026 Guide to Choosing an AI Agent Search API

When choosing a Search API, first identify the information your business needs. Then compare how each API retrieves that information, as well as its cost and speed. For example, industry research may require news, market data, and official statistics. Technical questions may require documentation for the relevant software version. Announcement monitoring may require filters for specific websites and publication dates. These needs determine which APIs are suitable for each use case. Price should only be compared after confirming that an API can meet your requirements.

If a team's tools need to search for webpages, market data, industry statistics, and other information on a regular basis, AnySearch is worth considering first. It covers publicly available information across the web and data from 20+ specialized domains. Web searches, market data queries, and industry statistics queries all use the same Search interface. This allows developers to reuse the same code for sending requests and handling results. When adding new types of queries, developers only need to provide the relevant parameters listed in the API catalog.

Different projects may have different priorities. Announcement monitoring places greater importance on filtering by website and date, while organizing information may require reading large amounts of webpage content. The following sections first establish selection criteria based on these needs, then compare five services. AnySearch's unified integration approach will be explained through a research case study and actual code examples. Pricing and plans will be discussed later.

Identify What You Need Before Comparing Search APIs

Can the API actually retrieve the information you need?

First, list the information your answers must be based on. For example, analyzing oil price changes may require price quotes, historical prices, and inventory data. Explaining new features in a software release requires official documentation for the relevant version. Relevant search result titles only indicate that a potentially useful source has been found. Whether the API can retrieve the required data or source content determines whether it is suitable for the task.

Some information can be obtained through additional searches or by reading webpage content. Other information requires a separate data service. When evaluating an API, first check whether missing information can be retrieved through additional requests. If it can, calculate the extra request and processing costs. If critical information remains unavailable, you will need to replace or add another data source. This helps avoid discovering only after integration that the system cannot complete its main tasks.

Can API parameters restrict sources and dates?

A requirement such as "search only for announcements published on specific websites in the past seven days" requires the API to filter results by website and date. Simply including these conditions in the search query does not guarantee that all results will meet them.

If these restrictions are business requirements, the first step is to check whether the API provides the corresponding parameters and which types of results they apply to. AnySearch's current general Search API does not provide unified site and date filtering parameters. For specialized searches, parameters depend on the capabilities defined for each search type. Exa, Firecrawl, and Tavily offer related filtering features and are worth considering for these tasks.

How much webpage content needs to be read after finding the links?

If a search returns ten pages but only two need to be read, the results can first be filtered, followed by content extraction from the key pages. If nearly all ten pages need to be passed to the model for reading, it is worth comparing services that return webpage content as part of their search results. These two approaches affect the number of requests, content retrieval costs, and the amount of content passed to the model.

File formats also affect API selection. For example, AnySearch's Extract API can retrieve webpage content but does not currently process PDFs or other binary files. If the key sources are mainly PDFs, the project will also need suitable document-reading capabilities.

Do usage costs and response times meet business requirements?

Once the information and functional requirements are met, total costs, latency, and request rates can be compared. QPS (Queries Per Second) determines how many search requests an API can process per second, while latency directly affects the user experience.

These four checks should narrow down the list of candidates. For example, projects that require strict filtering by website should first look at filtering parameters. Projects that need to read large amounts of webpage content should first compare content retrieval methods. Projects involving research across multiple domains should focus on specialized data coverage and integration effort. Prices should only be compared among candidates that meet these requirements.

Which Use Cases Are the Five Search APIs Best Suited For?

The table below compares the five services in terms of information retrieval, query controls, and integration requirements. It helps teams narrow down their options based on their specific tasks.

Sources: Official websites of AnySearch, Brave, Exa, Firecrawl, and Tavily.

When strict website and date requirements apply, an additional check is needed. Tavily requires filter_by_published_date to filter results strictly by publication date. Pages with unknown publication dates are also excluded. Exa has parameter restrictions in some modes, while Firecrawl's tbs time filter applies only to web results. Therefore, the specific search mode and parameters used need to be checked together.

The choice of service depends first on the task the team needs to complete. For research tasks that repeatedly combine specialized information such as market data and statistics, the main considerations are AnySearch's data coverage and unified integration. For tasks that mainly involve web searches and reading webpage content, the content retrieval methods offered by Exa, Firecrawl and Tavily are worth comparing. Teams that prefer Brave's independent web index can further compare its two interfaces: result lists and LLM Context. When multiple services offer overlapping features, the next selection criteria should be how much webpage content needs to be read, which parameters are required, and the total cost.

AnySearch's Advantage: Search Webpages and Specialized Data Through One Interface

Reuse Existing Integration Code When Adding New Types of Information

Suppose a team is developing a research tool that initially searches only industry news but later needs to include crude oil prices, grain statistics, and policy documents. If each type of information requires a separate service, the team usually needs to handle authentication, request formats, errors, and returned data separately for each service. AnySearch brings its supported general and specialized searches together under one Search interface. Developers can reuse existing code for sending requests, handling errors, and saving results, with changes mainly needed to the query content and specialized parameters.

On the server side, AnySearch integrates general search with specialized data sources, then organizes and ranks the results. Developers access these integrated capabilities through a unified interface without having to connect to each underlying service individually. However, the development team still needs to plan the query sequence based on the research question and check whether the dates, units, and coverage of the returned information meet the requirements. Unified integration reduces repetitive API adaptation work, but the research workflow still needs to be designed separately.

This integration approach becomes more valuable when a team needs to keep adding information sources to a research tool. If new market data or statistical queries are already available in the capability catalog, the existing code can continue to be used. If the tool only needs general web search, the coverage of specialized domains is less important when choosing an API.

How Can a Single Research Task Use These Capabilities?

An internal test conducted on November 5, 2026, used a hypothetical conflict in the Strait of Hormuz as its scenario and required research into market data, energy, grain, and congressional actions. This example illustrates the process of gathering information across multiple domains. The events and price increases in the scenario are assumptions, not verified news. The following three steps are taken from the test records to show how AnySearch can be used to collect research materials.

Step 1: Search for background reports.

Start with a general search to find relevant reports and understand the events and organizations involved in the research question. These findings can then guide searches for specific data and documents.

Step 2: Retrieve market data for specific instruments.

The test used market data queries to retrieve price snapshots for WTI crude oil, Brent crude oil, and gold, along with their seven-day highs and lows.

Step 3: Retrieve original sources for citation.

The grain-related research also required official supply and demand materials. Subsequent records included the retrieval of the FAO's Cereal Supply and Demand Brief. The archived version was dated October 2, 2026. It gave a 2026 wheat production forecast of 813.9 million tonnes and a 2026/27 rice forecast of 552.5 million tonnes, with the latter expressed on a milled basis. When citing these historical materials, the publication date, forecast year, and unit of measurement should all be retained.

These three steps follow a simple process: search for background information, retrieve market data, and read original sources. In the code, the first two steps can share the same request-sending and result-handling logic. Extract can then be called when original webpage content is needed. This allows the team to focus development work on query conditions and information processing when adding new types of searches, while reusing the existing integration code.

However, this research did not retrieve all the data required for the task. For oil prices, for example, the returned results included price quotes and seven-day highs and lows, but not the daily prices for those seven days. A daily oil price chart would therefore require additional data retrieval. The high and low values alone cannot replace the daily prices.

This also shows why API selection should not stop at checking whether an API "supports market data queries." The returned data must also be suitable for the specific task. A practical way to evaluate this is to use a real business question and check what data is returned, what is still missing, and whether the missing information can be obtained through additional queries. The full queries and results are available in the case study.

How to Integrate: From General Search to Specialized Queries

To implement the queries described above in code, the first step is to distinguish between general web searches and specialized queries. For a general web search, only the query field needs to be submitted. It specifies what to search for. When a specific specialized query is needed, the tag and params fields can also be added. The tag selects the search capability, while params specify the target and search conditions. For example, when retrieving crude oil prices, the tag selects the market data query, while the parameters specify the instrument and time range.

Tags and parameters can be found in the capability catalog. The catalog lists available capabilities and their parameter requirements. Browsing the catalog does not consume search quota. Once a capability is selected, the request is still sent to the same Search endpoint.

A Real WTI Crude Oil Query Example

The request example below shows a direct API call. In an MCP-enabled Agent environment, a single natural-language prompt can be used to retrieve the answer through MCP. For details on choosing and using MCP, see the MCP selection guide.

The request body below comes from an actual API call made on November 5, 2026. finance.quote selects the market data query, CLUSD specifies WTI crude oil, and 7d sets the seven-day range. Before running the example, set the API key as the ANYSEARCH_API_KEY environment variable.

import json
import os
from urllib.error import HTTPError
from urllib.request import Request, urlopen

payload = {
    "query": "WTI crude oil latest price and last 7 days",
    "tag": "finance.quote",
    "params": {"type": "commodity", "symbol": "CLUSD", "period": "7d"},
    "max_results": 7,
}
request = Request(
    "https://api.anysearch.com/v1/search",
    data=json.dumps(payload).encode("utf-8"),
    headers={
        "Authorization": f"Bearer {os.environ['ANYSEARCH_API_KEY']}",
        "Content-Type": "application/json",
    },
    method="POST",
)

try:
    with urlopen(request, timeout=30) as response:
        result = json.load(response)
except HTTPError as error:
    request_id = error.headers.get("X-Request-ID", "unknown")
    raise RuntimeError(
        f"HTTP {error.code}; request_id={request_id}"
    ) from None

if result.get("code") != 0:
    raise RuntimeError(
        f"API failure; request_id={result.get('request_id', 'unknown')}"
    )

sources, seen = [], set()
for item in (result.get("data") or {}).get("results") or []:
    url = (item.get("url") or "").strip()
    if not url.startswith(("https://", "http://")) or url in seen:
        continue
    seen.add(url)
    sources.append({
        "title": item.get("title") or "",
        "url": url,
        "text": item.get("content") or item.get("snippet") or "",
    })

print(json.dumps(sources, ensure_ascii=False, indent=2))

After sending the query, the code first checks whether the request was successful. It then saves the title, URL, and available text from each result, skipping any duplicate URLs. For other specialized queries, only the query and params fields in the payload need to be updated according to the catalog. The remaining code for sending requests and processing results can be reused.

The historical request below was successful. One result is shown with short fields, while longer content and metadata are omitted. The price of $89.31 per barrel and the seven-day range are both examples from that specific response.

{
  "code": 0,
  "request_id": "c55b12a8-785d-4b90-98fc-6870049731bd",
  "message": "success",
  "data": {
    "results": [
      {
        "title": "WTI Crude Oil (CLUSD)",
        "url": "https://site.financialmodelingprep.com/?ref=quote-CLUSD",
        "snippet": "$89.31/barrel ▲1.44% · 7d: High $104.99 / Low $86.66"
      }
    ]
  }
}

The url field in the results contains the source link, while snippet provides a short summary. If the summary is not enough to answer the question, the returned content field can be examined. If this field is missing or still lacks the necessary information, the original webpage can then be read.

Call Extract When Webpage Content Is Needed

When the search results are not enough to answer the question and the original webpage needs to be read, a request can be sent to POST /v1/extract with {"url":"target page URL"}. The webpage content can then be read from the returned data.content field.

This approach is suitable for tasks that require a closer look at only a few results: search and filter the sources first, then extract content from the key pages. If most of the pages returned by a search need to be read, search options that return webpage content alongside the results are worth comparing.

The supported file formats also need to be considered. Extract currently accepts URLs only and does not process PDFs or other binary files. The content limit is 50,000 Unicode characters. If the main sources are PDFs, additional document-reading capabilities will be needed.

General searches and specialized queries can share the same basic request and result-handling code. Extract requests can be added when the original webpage content needs to be read. Once the number of searches and extraction requests required for a business task has been determined, the API usage cost can be estimated.

Pricing and Response Time: How to Assess Whether a Service Is a Good Fit

The search and content extraction methods discussed above both require API calls. The number of calls and the way they are made affect the overall cost. The following sections first calculate how much these calls cost, then examine how long users may have to wait for search results.

Compare Per-Search Costs, Including Content Retrieval

The credits shown in the table below are the respective billing units used by each service. Credit amounts cannot be compared directly across services and must be converted into actual costs.

Pricing was verified as of November 6, 2026.

Based on the table above, AnySearch Pro has a lower base cost per search than Tavily Basic PAYG, the listed Exa modes, and Brave Search. In addition, purchased calls do not expire at the end of the month. This allows teams with gradually increasing usage or concentrated usage during specific projects to use their remaining balance as needed.

For consistently high usage, monthly plans should also be considered. For example, Firecrawl Standard costs $99 per month and includes 100,000 credits. If all credits are used for standard Search and each search uses the full allowance of up to 10 results, the plan can support approximately 50,000 searches, at an average cost of $1.98 per 1,000 searches. If the credits are not fully used, the average cost per actual search will increase. Therefore, AnySearch's non-expiring call packages are worth considering when usage fluctuates, while monthly plans should also be compared when usage is high and stable.

However, the comparison above covers only the base cost of a single search. If a task also requires follow-up searches, content extraction, and model calls, all these costs need to be added together to determine the actual cost of completing the task.

Take AnySearch Pro as an example. Suppose 100 tasks are run each day, with each task requiring five successful, non-empty Search calls and two valid Extract calls, for a total of 700 billable calls per day. If all calls are billed at the Pro rate, the daily cost is $2.10. Over ten consecutive days, 7,000 calls would cost $21, or an average of $0.021 per task, excluding model costs.

This budget is only an illustration of the calculation method, not the actual bill for the research case discussed earlier. Actual spending will vary depending on the number of follow-up searches and extraction requests. During testing, the number of searches and extraction requests used by each task should therefore be recorded and used as the basis for budget planning.

How Long Does a Single Search Take?

In addition to cost, the time between submitting a query and receiving search results also matters. After search results are returned, the system may still need to read webpages and wait for the model to generate an answer. Therefore, search latency does not represent the total waiting time. The following comparison focuses on the time required for the search step.

In a test conducted on November 4, 2026, 100 requests were recorded for each service. The measurements cover the time taken to return summaries, snippets, or highlights, excluding webpage content extraction. All values are shown in seconds. P95 indicates the time within which approximately 95% of requests were completed, showing how long slower requests may take.

Taking AnySearch as an example, the average search response time in this test was approximately 1.8 seconds, while the P95 was approximately 2.9 seconds. This means that waiting time should not be estimated based on the 1.8-second average alone; additional time should be allowed for slower requests. If a product requires 95% of searches to complete within 2 seconds, the sample in this test did not meet that requirement.

These figures reflect this test only. The specific test setup and scope are described in the case study. Before production integration, the time spent on subsequent webpage reading, retries, and answer generation should also be recorded to determine the actual end-to-end waiting time from query submission to answer delivery.

How to Choose Between AnySearch Free, Pro, and Enterprise

The previous sections compared different Search services in terms of information coverage, cost, and response time. If AnySearch is selected for integration, the next step is to choose a plan. The following section first compares the actual results returned by Free, Pro, and Enterprise accounts for the same query, then explains which plan is suitable based on usage limits, request rates, and service terms.

Compare the Results Returned by AnySearch Free, Pro, and Enterprise for the Same Query

In the earlier Strait of Hormuz test, all three account types submitted the same query, each requesting a maximum of 10 results. The Enterprise account used its default settings. The customized plan discussed below, by contrast, defines search and output requirements according to the specific project. The initial records from November 5, 2026, are shown below:

In this test, Free returned more text, but some of it came from duplicate reports. Pro and the Enterprise plan's default configuration returned exactly the same results. Therefore, these records do not provide evidence that upgrading necessarily improves content quality. Each plan was called only once, and the calls were made at different times. The response times in the table reflect only those individual measurements. Plan selection should also take into account the confirmed usage limits, request rates, and service terms discussed below.

When Are AnySearch Free, Pro, and Enterprise Suitable?

• Free: Suitable for integration and small-scale workloads with up to 1,000 requests per day and peak usage of no more than 10 QPS. The daily quota resets at 08:00 Beijing time and does not carry over. Free can continue to be used as long as its quota and features meet business needs.
• Pro: Suitable when the daily free quota is insufficient or a request rate of up to 20 QPS is required. Additional calls can be purchased at $3 per 1,000 calls. Purchased calls do not expire, making Pro suitable for gradually increasing paid usage as business needs grow. Any available Pro balance is used first. Therefore, budgets should not assume that the free quota will be used up before paid calls are deducted.
• Enterprise: Suitable when higher request rates, separate usage allocations for different projects, customized features, or contractually agreed service commitments are required. The default limit is 50 QPS and can be adjusted through an order. Enterprise supports per-key usage allocation and customization of search scope, ranking, output fields, formats, deduplication rules, and integration methods.

What Can Be Customized in Enterprise? An Energy Storage Tender Data Integration Example

The customization options for output fields, deduplication, and integration can be illustrated with an energy storage tender use case. Suppose an equipment company wants to add newly announced tender projects to its internal business opportunity database every day. Beyond finding announcements, the system also needs to determine which information to save and how to handle multiple announcements for the same project.

The requirements could be defined as follows: search for energy storage tenders in Jiangsu, Zhejiang, and Anhui announced within the past 30 days; include the project name, procuring entity, location, announcement date, bid submission deadline, and original source URL in each result; consolidate duplicate announcements for the same project; and deliver the results in the format required by the business opportunity database.

AnySearch has confirmed that its search capabilities and API integration can be customized to meet these requirements. During procurement, both parties can agree on the search scope, required fields, deduplication rules, and integration format. This is an example of an enterprise customization requirement. The specific features need to be agreed upon for each project. These customized fields are not automatically included in the standard Search service.

In addition to specifying which information should be returned, enterprise procurement agreements usually need to define availability, response times, and support response targets for different types of issues. The following service metrics have been confirmed for the Enterprise plan. The specific terms should be checked against the agreement during procurement:

Monthly average latency and P95 are different metrics. Support response times also do not indicate how long issue resolution will take. The formal agreement governs the specific definitions, exclusions, and compensation terms.

Therefore, when the standard API already meets business requirements, Free or Pro can be selected based on usage limits and request rates. Enterprise is worth considering when customized information processing rules are needed, as in the tender data integration example, or when availability and support response commitments need to be included in a formal agreement.

How to Make the Final Choice

If a team's regular research requires a combination of webpages, market data, industry statistics, and policy documents, AnySearch is worth considering first. These projects require ongoing access to multiple types of information. AnySearch allows supported queries to reuse the same basic request and result-handling code. The same integration approach can also be used as new types of information are added. Before integration, representative real-world queries should be tested to confirm that the required instruments, metrics, and fields are available.

For projects with these requirements, Pro makes it easier to increase usage gradually when call volume fluctuates. It costs $3 per 1,000 calls, and purchased calls do not expire. If custom output fields, deduplication rules, or contractual service commitments are also required, the Enterprise plan is worth considering.

If a project has different priorities, the choice of API should reflect those priorities. When filtering by website and date is essential, first compare the relevant parameters offered by Exa, Firecrawl and Tavily. When large amounts of webpage content need to be read, compare the costs of search options that include webpage content in their results with the costs of separate content extraction. When an independent web index is preferred, compare Brave's result-list interface with its LLM Context interface.

If the main sources are PDFs, document-reading capabilities should be checked first. If search results need to be written directly into a business system, confirm that the required fields and output formats are supported. If these requirements are not met, additional components or customized services may be needed.

Finally, test the shortlisted services with several real business queries. Before testing, define the information required for each query, along with any source, date, or version requirements. During testing, record usage for search requests, webpage content retrieval, retries, and model calls. Only after confirming that the required information can be retrieved should total cost and completion time be compared. If key information remains unavailable, additional data sources or a different solution will be needed. This approach ensures that the final choice is based on actual business results.

To get started with AnySearch, review the Search API and capability catalog, then use the free quota included in the Free plan to complete a representative task. During task execution, the system automatically calls Extract to retrieve the full content of a webpage whenever more detailed reading is required. The appropriate plan can then be selected on the pricing page based on actual task requirements and usage.

Common Integration Questions

Q1：Does a General Search Also Require a tag?

No. A general web search only requires the query field. For a specialized query, select the relevant tag from the capability catalog and provide the corresponding params. Parameters may vary across specialized capabilities and should follow the definitions for each one.

Q2：Is Extract Still Needed When Search Results Already Include the content Field?

First, check whether the content field already includes the required figures or passages. If it contains enough information, there is no need to extract the same page again. If essential information is still missing and the source needs to be examined in more detail, Extract can be called. Whether the content comes from search results or a separate extraction request, the source URL should be retained for verification.

Q3：When Should the API or MCP Be Used?

Use the API when a program needs to control the order of requests, caching, and data processing. MCP is suitable when working in an Agent environment that supports MCP and the Agent needs to invoke tools. This article demonstrates API integration through direct HTTP requests from a program.