Search Autocomplete APIs — Google, Bing, and Alternatives

Search autocomplete data powers keyword research, content strategy, SEO tools, and ad targeting. The "People Also Search For" and suggestion dropdowns contain intent signals that are hard to get any other way. This guide covers every search autocomplete API available in 2026, from Google's own services to third-party providers, with pricing and code examples.

Key Takeaways

• Google's Autocomplete API is not officially available — third-party providers reverse-engineer it
• Serper.dev exposes autocomplete at $0.50-1.00 per 1K queries via its Google endpoint
• Brave Search API offers a dedicated Suggest endpoint at $5/1K with 1K free/month
• Bing Autosuggest API runs on Azure at $1.50-3.00/1K transactions
• SearchHive DeepDive includes autocomplete-like keyword expansion as part of its research API
• Free options exist — manual scraping via browser automation, or rate-limited API tiers

Why Autocomplete Data Matters

Search autocomplete suggestions reflect what millions of people are actively typing. This data has several high-value use cases:

• Keyword research: Discover long-tail queries your audience is searching for
• Content gap analysis: Find questions your competitors are answering that you aren't
• Ad targeting: Bid on high-intent autocomplete suggestions
• Product naming: See how people describe products in natural language
• Trend detection: Track how autocomplete suggestions change over time

The challenge: Google doesn't offer an official autocomplete API. You have to use alternatives.

Google Autocomplete via Third-Party APIs

Serper.dev

Serper.dev provides a dedicated autocomplete endpoint that returns Google's suggestion dropdown results.

Pricing: Same as search — $0.50-1.00/1K at volume, 2,500 free credits on signup.

import requests

response = requests.get(
    "https://google.serper.dev/autocomplete",
    headers={"X-API-KEY": "your-api-key"},
    params={"q": "python web scraping"}
)
for suggestion in response.json().get("1", []):
    print(suggestion)

The response returns an array of suggestion strings. It is fast (under 1 second) and reliable. At Scale tier ($1,250 for 2.5M credits), the cost drops to $0.50/1K queries.

Tavily

While Tavily is primarily a search API for AI agents, it returns related search terms in its response that serve a similar function to autocomplete.

Pricing: $0.008/credit, 1,000 free/month.

from tavily import TavilyClient

client = TavilyClient(api_key="your-api-key")
result = client.search(query="kubernetes monitoring tools", max_results=5)
print("Answer:", result["answer"])
for r in result["results"]:
    print(r["title"])

Tavily does not have a dedicated autocomplete endpoint. The related queries in the response are derived from the search results, not from Google's autocomplete service.

Bing Autosuggest API

Bing offers an official Autosuggest API through Azure Cognitive Services. This is the only major search engine with a first-party autocomplete API.

Pricing (Azure):

• S1: $3/1K transactions
• S2: $2/1K transactions (after 1K)
• S3: $1.50/1K transactions (after 50K)
• 1,000 free transactions/month

import requests

headers = {"Ocp-Apim-Subscription-Key": "your-azure-key"}
response = requests.get(
    "https://api.bing.microsoft.com/v7.0/suggestions",
    headers=headers,
    params={"q": "best rust web framework"}
)
for group in response.json()["suggestionGroups"]:
    for s in group["suggestions"]:
        print(s["query"])

Bing's autocomplete differs from Google's. Bing tends to show more branded and navigational suggestions, while Google leans informational. For keyword research, getting both is ideal.

The API is reliable, well-documented, and backed by Azure SLAs. The main limitation is that Bing's search volume is smaller than Google's, so the suggestions reflect a different user base.

Brave Search API — Suggest Endpoint

Brave offers a dedicated Suggest endpoint as part of its search API suite.

Pricing: $5/1K requests (shares the same $5/month free credits as search). 50 queries per second.

import requests

headers = {"X-Subscription-Token": "your-brave-key"}
response = requests.get(
    "https://api.search.brave.com/res/v1/suggest",
    headers=headers,
    params={"q": "machine learning tutorials"}
)
for s in response.json().get("suggestions", []):
    print(s.get("query", s))

Brave's suggestions come from its own index and user query data. They differ from both Google and Bing, which makes them useful as a third data point.

The $5/month free credits give you 1,000 suggestions per month at no cost. Combined with Bing's free tier, you get 2,000 free autocomplete queries monthly from two independent sources.

SearchHive DeepDive

SearchHive's DeepDive API handles research tasks that include keyword expansion and related query discovery as part of its broader research capabilities.

Pricing: Credits shared across SwiftSearch, ScrapeForge, and DeepDive.

• Free: 500 credits
• Starter: $9/month for 5,000 credits
• Builder: $49/month for 100,000 credits

from searchhive import DeepDive

client = DeepDive(api_key="your-api-key")
result = client.research(
    query="best vector database for ai applications",
    depth="standard",
    include_keywords=True
)
print("Main findings:", result.get("summary", "")[:300])
for kw in result.get("related_keywords", [])[:10]:
    print(f"  {kw}")

DeepDive goes beyond autocomplete by combining suggestion data with actual search results and content analysis. The related_keywords field includes autocomplete-style suggestions plus semantically related terms discovered from the content.

Other Autocomplete Data Sources

Datamuse API (Free)

Datamuse provides a free linguistic API that includes word completion and related word suggestions. It is not search-engine-specific but useful for content and copywriting applications.

import requests
response = requests.get(
    "https://api.datamuse.com/sug?s=python+web+fra"
)
for r in response.json():
    print(r["word"], r["score"])

No API key needed, no rate limits documented (be respectful), free forever. Returns word completion suggestions, not search autocomplete.

Google Trends (Limited)

Google Trends shows "Related Queries" for search terms, which overlaps with autocomplete data. It's free but limited to hourly data with daily granularity. Not an API in the traditional sense — more of a data source.

Manual Browser Scraping

You can scrape Google's autocomplete directly by automating a browser, but this violates Google's Terms of Service and your IP will get rate-limited quickly. Not recommended for production use.

Comparison Table

Best Practices for Autocomplete Data

1. Combine multiple sources. Google, Bing, and Brave autocomplete each reflect different user bases. Cross-referencing gives you a more complete picture.

2. Use letter expansion. Query "python web scraping a", "python web scraping b", etc. to get alphabetically expanded suggestions. This is how most keyword tools discover long-tail variants.

3. Cache results aggressively. Autocomplete data changes slowly. Cache for 24-48 hours to avoid redundant API calls.

4. Deduplicate across engines. The same suggestion often appears on Google, Bing, and Brave. Deduplicate before analysis.

5. Track changes over time. Store autocomplete results weekly. New suggestions signal emerging trends; disappearing ones signal declining interest.

Get Started

For keyword research and SEO workflows, combine Serper.dev ($0.50/1K for Google autocomplete) with Bing's free tier (1,000/month). If you need autocomplete data as part of a broader search and research pipeline, SearchHive bundles it with web search and content scraping at $49/month for 100K credits. Start with the free tier — 500 credits, no credit card required. See the full docs.