Microsoft pulled the plug on the Bing Search API on August 11, 2025. If your AI pipeline, search feature, or agent relied on it, you already know the pain.
The official migration path? "Grounding with Bing Search" inside Azure AI Foundry. That's not a drop-in replacement. It's an entire platform commitment with resource groups, model deployments, and Azure lock-in. For most developers, that's a non-starter.
The good news: several alternatives have filled the gap. Some are better than what Bing offered. This guide covers the 7 best Bing Search API alternatives for 2026, with honest pros, cons, and pricing for each.
Why Was the Bing Search API Discontinued?
Microsoft announced the retirement on May 15, 2025. Three months later, every Bing Search sub-API went dark: Web Search, Image Search, News Search, Video Search, Autosuggest, Spell Check, Entity Search, Visual Search, Custom Search, and Local Business Search. All gone.
The reasoning? Microsoft wants search embedded inside AI agents, not exposed as a raw data endpoint. Makes sense for Microsoft's strategy. Less sense for the thousands of developers who built products on top of the API and had roughly 90 days to migrate.
The timing was messy too. API creation was quietly disabled in March 2025, weeks before any public announcement. Developers discovered their apps breaking before Microsoft bothered to explain why.
What to Look for in a Bing Search API Replacement
Before jumping to alternatives, think about what you actually used Bing for:
- Just search results? You need a search API that returns links, snippets, and metadata (Brave, SerpAPI)
- Content for AI pipelines? You need a tool that returns full-page content in LLM-ready formats, not just snippets (ScrapeGraphAI, Firecrawl)
- Structured data extraction? You need AI-powered extraction that pulls specific fields from web pages (ScrapeGraphAI)
- Multi-engine coverage? You need access to Google, Bing, and other indexes from one API (SerpAPI)
Most Bing users were in the second camp: feeding search results into AI applications. If that's you, a plain search API is only half the solution. You still need to fetch, render, and extract the actual page content. Tools like ScrapeGraphAI handle that entire chain in a single call.
The 7 Best Bing Search API Alternatives
1. ScrapeGraphAI
ScrapeGraphAI takes a fundamentally different approach from Bing. Instead of returning links and snippets, its SearchScraper endpoint searches the web and extracts structured data in one API call. You describe what you want in natural language, and the AI finds relevant pages, reads them, and returns exactly the data fields you asked for.
This is the missing link that Bing never provided. With Bing, you got search results, then had to fetch each page, parse the HTML, and extract what you needed. That's three or four steps. ScrapeGraphAI collapses it into one.
from scrapegraph_py import Client
client = Client(api_key="your-api-key")
result = client.searchscraper(
user_prompt="Find the top 5 open-source LLMs released in 2026 with their parameter counts and licensing",
schema={
"type": "object",
"properties": {
"models": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": {"type": "string"},
"parameters": {"type": "string"},
"license": {"type": "string"},
"release_date": {"type": "string"}
}
}
}
}
}
)
for model in result["result"]["models"]:
print(f"{model['name']} - {model['parameters']} - {model['license']}")No links to click. No pages to fetch. No HTML to parse. You get structured JSON back with exactly the fields you defined.
Beyond SearchScraper, ScrapeGraphAI also offers SmartScraper (extract data from any URL) and SmartCrawler (crawl entire sites with AI extraction). Together, they cover every use case Bing handled plus the extraction layer Bing never had.
Key Benefits
- Search + extraction in one API call with natural language prompts
- Structured JSON output matching your custom schema
- SmartScraper for single-page extraction, SmartCrawler for multi-page crawling
- Python and JavaScript SDKs, REST API
- Native LangChain, LangGraph, and MCP protocol integration
- Fixed credit pricing with no surprises
Pricing
- Free: $0/month
- Starter: $17/month
- Growth: $85/month
- Pro: $425/month
- Enterprise: Custom
SearchScraper costs 30 credits per query, SmartScraper costs 10 credits per page, Markdownify costs 2 credits per page. You know exactly what you'll spend.
Pros & Cons
Pros:
- Replaces the entire Bing pipeline (search + fetch + parse + extract) with one call
- AI extraction adapts to any website without selectors
- Predictable credit-based billing
- Great for RAG, AI agents, and competitive intelligence
Cons:
- Not a traditional search index (uses web search under the hood)
- Advanced schema design takes some practice
Rating
9.5/10
If you used Bing to feed structured data into AI applications, ScrapeGraphAI is the best replacement. It does what Bing did and adds intelligent extraction on top. The pricing is transparent and the developer experience is excellent.
2. Brave Search API
Brave runs its own independent search index with 30+ billion pages. No Bing. No Google. If you picked Bing specifically because you wanted an alternative to Google's index, Brave is the closest spiritual successor.
The API returns standard SERP JSON with web results, images, news, and videos. They also have an AI Grounding endpoint optimized for LLM context.
Key Benefits
- Independent 30B+ page index, crawled by Brave
- SOC 2 Type II certified with no user tracking
- Search Goggles for customizing result ranking and domain filtering
- AI Grounding endpoint for LLM-ready results
- Specialized endpoints for images, videos, news, suggest, and spellcheck
Pricing
- Free: ~1,000 queries/month
- Paid: $5-9 per 1,000 requests
- Up to 50 queries/second on Pro AI plan
Pros & Cons
Pros:
- Truly independent index, not reselling Bing or Google data
- Strong privacy guarantees (no tracking, SOC 2)
- Covers most of Bing's sub-APIs (web, image, news, video, suggest)
- Affordable per-request pricing
Cons:
- Returns raw SERP JSON, not full page content
- Smaller index than Google (but growing)
- No built-in content extraction for AI pipelines
- You'll need a scraping tool alongside it for full page data
Rating
8/10
Brave is the most direct Bing replacement on this list. Same concept (search index + API), better privacy, independent infrastructure. But like Bing, it returns links and snippets, not full content. For AI pipelines, you'll still need a separate extraction step.
3. Firecrawl
Firecrawl focuses on turning web pages into LLM-ready content. Its Search endpoint finds pages and extracts their full content in one call, returning markdown or structured JSON. It also handles crawling, scraping, and even has an Agent endpoint for autonomous multi-step research.
The open-source version (85k+ GitHub stars) can be self-hosted, which matters for teams with compliance requirements.
Key Benefits
- Search + full-page extraction in one API call
- Output as clean markdown or structured JSON
- Open source with self-hosting option
- Browser Sandbox for complex interactions (auth, forms, multi-step flows)
- Agent endpoint for autonomous data gathering
Pricing
- Free: 500 credits
- Hobby: $16/month (3,000 credits)
- Standard: $83/month (100,000 credits)
- Growth: $333/month (500,000 credits)
- Enterprise: Custom
Pros & Cons
Pros:
- Full page content extraction, not just snippets
- Self-hosting for compliance-sensitive teams
- Browser Sandbox handles authenticated and dynamic sites
- Large community and active development
Cons:
- Token-based pricing makes cost prediction harder
- AI extraction requires additional configuration or LLM calls
- More expensive than Brave for simple search queries
- Less structured data output compared to ScrapeGraphAI
Rating
7.5/10
Firecrawl is a solid option for teams that need full page content from the web. The self-hosting capability is a real differentiator. But the extraction intelligence isn't as deep as ScrapeGraphAI's, and the token pricing can surprise you at scale.
4. Tavily
Tavily was built from the ground up for RAG applications and AI agents. Results come back as AI-optimized snippets with relevance scores, ready to inject into an LLM's context window without formatting.
The LangChain integration is native and takes minutes to set up, which explains why it's popular in that ecosystem.
Key Benefits
- AI-optimized search results ranked for LLM context
- Native LangChain and LangGraph integration
- Flat $0.008 per credit pricing
- Extract, Crawl, and Map endpoints beyond basic search
- Fast response times for real-time agent workflows
Pricing
- Free: 1,000 credits/month
- Paid: Starting at $30/month
- $0.008 per credit, flat rate
Pros & Cons
Pros:
- Results formatted specifically for LLM consumption
- Predictable pricing with flat credit cost
- Fastest integration path for LangChain-based agents
- Good for RAG prototyping
Cons:
- Returns optimized snippets, not full structured data
- Smaller feature set than ScrapeGraphAI or Firecrawl
- No self-hosting option
- Less useful if you need custom data schemas
Rating
7/10
Tavily is a quick win for LangChain developers building RAG prototypes. The AI-optimized output saves formatting time. But if you need structured data extraction beyond snippets, you'll outgrow it fast.
5. Exa
Exa does search differently. Instead of keyword matching, it uses embeddings-based semantic search to find pages that are conceptually related to your query. Feed it a URL and it returns similar pages. Feed it a natural language description and it finds matching content by meaning, not keywords.
Key Benefits
- Embeddings-based semantic search (understands meaning, not just keywords)
- Find Similar endpoint for discovering related content from a URL
- Answer endpoint with summarized responses and citations
- Research endpoint for automated deep research
- Strong for content discovery and recommendation features
Pricing
- Free: 1,000 credits
- Paid: $49 for 8,000 credits
- Variable credit consumption (75-750+ credits per search)
Pros & Cons
Pros:
- Semantic search finds conceptually relevant results that keyword search misses
- Find Similar is unique and useful for competitive research
- Good for research tools and content discovery
- Answer endpoint provides ready-made summaries
Cons:
- Credit consumption varies wildly per query (hard to budget)
- No full page extraction built in
- More expensive per query than most alternatives
- Smaller coverage than traditional search indexes for niche topics
Rating
7/10
Exa shines when you need semantic discovery rather than keyword matching. The Find Similar feature has no equivalent elsewhere. But variable credit consumption makes budgeting difficult, and you'll need a separate tool for content extraction.
6. SerpAPI
SerpAPI doesn't build its own index. It scrapes Google, Bing, DuckDuckGo, Yahoo, Baidu, and 25+ other search engines in real-time and returns structured JSON of the full SERP: organic results, ads, knowledge panels, featured snippets, "People also ask," local packs, and more.
If you specifically need Bing SERP data even after the API shutdown, SerpAPI still scrapes Bing's public results.
Key Benefits
- Access 25+ search engines from one API
- Full SERP parsing (organic, ads, knowledge panels, featured snippets)
- Real-time results from live search engines
- Still provides Bing results via scraping
- Useful for SEO monitoring and competitive analysis
Pricing
- Free: 100 searches/month
- Starter: $50/month (5,000 searches)
- Higher tiers available for volume
Pros & Cons
Pros:
- Multi-engine access in one API (including Bing, Google, DuckDuckGo)
- Richest SERP data: ads, knowledge panels, featured snippets
- Real-time results, always current
- Best option if you need actual Bing SERP data post-shutdown
Cons:
- Returns SERP metadata only, not full page content
- More expensive than dedicated single-engine APIs
- Reliance on scraping public SERPs means potential instability
- No AI extraction or LLM-ready output
Rating
6.5/10
SerpAPI is the right tool if you need SERP data from multiple engines, especially for SEO and competitive monitoring. But it only gives you search result metadata, not the actual content. For AI pipelines, you'll need something else alongside it.
7. Google Custom Search API
Google's Programmable Search Engine (formerly Custom Search API) is worth mentioning as the obvious large-index alternative. You define a custom search engine scoped to specific sites or the entire web, and query it programmatically.
Key Benefits
- Backed by Google's massive search index
- Customizable search scope (specific sites or full web)
- Image search support
- Well-documented with official client libraries
Pricing
- Free: 100 queries/day
- Paid: $5 per 1,000 queries (up to 10,000/day)
Pros & Cons
Pros:
- Largest search index available
- Reliable infrastructure from Google
- Straightforward REST API
- Free tier good for testing
Cons:
- Hard limit of 10,000 queries per day
- Returns links and snippets, not full content
- Requires Google Cloud project setup
- Custom search engine configuration can be confusing
- No AI-specific features or LLM-ready output
Rating
6/10
It's Google search in an API, which covers the basic "find relevant pages" use case. But the daily limits are restrictive, there's no content extraction, and the configuration process is clunky. Fine as a fallback, but not built for modern AI workflows.
How They Compare: Quick Reference
| Alternative | Returns Full Content | AI Extraction | Own Index | Best For |
|---|---|---|---|---|
| ScrapeGraphAI | Yes (structured) | Yes | No | AI agents, RAG with structured data |
| Brave Search | No (snippets) | No | Yes | Privacy-first search, Bing replacement |
| Firecrawl | Yes (markdown) | Basic | No | Full-page content for AI pipelines |
| Tavily | No (snippets) | No | No | RAG prototyping, LangChain agents |
| Exa | No (snippets) | No | Yes | Semantic discovery, research tools |
| SerpAPI | No (SERP data) | No | No | Multi-engine SERP monitoring |
| Google CSE | No (snippets) | No | Yes | Basic web search with large index |
Which Alternative Should You Pick?
It depends on what you actually built on top of Bing.
If you fed Bing results into AI applications: ScrapeGraphAI is the strongest replacement. SearchScraper does what your old Bing pipeline did (search, fetch, parse, extract) in a single API call with structured JSON output. No glue code needed.
If you need a traditional search index: Brave Search API is the closest match to Bing. Independent index, similar SERP format, better privacy. Add ScrapeGraphAI's SmartScraper on top if you need to extract content from the results.
If you're building with LangChain: Tavily has the fastest integration path. Native support, AI-optimized snippets, predictable pricing. Pair it with ScrapeGraphAI when you need structured extraction.
If you need SERP data from multiple engines: SerpAPI is the only option that scrapes Bing, Google, and 25+ other engines. Good for SEO tools and competitive monitoring.
If you need semantic discovery: Exa's embeddings-based search finds things keyword search can't. Good for research tools. Pair with an extraction API for full content.
The Bing Search API retirement is a hassle, but the tools that replaced it are honestly better for most AI use cases. Bing gave you links and snippets. The best alternatives give you structured, LLM-ready data in a single call.
Frequently Asked Questions
Why was the Bing Search API shut down?
Microsoft retired all Bing Search APIs on August 11, 2025, as part of a shift toward embedding search inside AI agents rather than exposing it as a raw API. The recommended migration is "Grounding with Bing Search" inside Azure AI Foundry, which requires a full Azure platform commitment.
Can I still get Bing search results after the API shutdown?
Yes. SerpAPI scrapes Bing's public search results in real-time and returns structured JSON. You won't get the same API format, but you'll get equivalent data.
What's the best Bing Search API alternative for RAG pipelines?
ScrapeGraphAI's SearchScraper is the most complete option. It searches the web, visits relevant pages, and extracts structured data matching your schema in one call. Tavily is a good lighter alternative if you only need search snippets for LLM context.
Is there a free alternative to the Bing Search API?
Several alternatives offer free tiers: ScrapeGraphAI (free plan), Brave Search API (~1,000 queries/month), Tavily (1,000 credits/month), Exa (1,000 credits), SerpAPI (100 searches/month), and Google Custom Search (100 queries/day).
Do I need a search API AND a scraping API?
If you only need links and snippets, a search API alone works. If you need the actual content from those pages for AI processing, you either need both or a tool like ScrapeGraphAI that combines search and extraction in one call.
Related Articles
- SearchScraper: AI-powered search and data extraction - How ScrapeGraphAI's SearchScraper endpoint works and when to use it
- Why AI Web Scraping Beats Search APIs for Data - Why search API snippets fall short for structured data and what to use instead
- Tavily vs ScrapeGraph: AI Search vs AI Scraping - Head-to-head comparison of search-first vs extraction-first approaches
- ScrapeGraph vs Exa: AI Search and Scraping Compared - How semantic search compares to AI-powered scraping for data access
- Top Exa Alternatives for AI-Powered Semantic Search - Roundup of the best tools for AI-optimized semantic search