Serper Alternative: Pricing, Features & AI Agent Support

TLDR: Choose Serper.dev for Google-only search, fast responses, and prepaid packs. Choose SERPHouse for Google, Bing, and Yahoo, device and city targeting, or scheduled batch jobs. Judge any Serper alternative on credits used, rate limits, and expiry.

Most teams pick a SERP API by the price on its homepage, then pay for that choice in parsing work for years. The affordable API is the one whose coverage, data shape, and billing model match your workload. Every Serper alternative looks similar in a demo and very different at 100,000 queries a month.

Serper.dev built its name on speed and simple Google queries. SERPHouse focuses on multi-engine coverage, device and city targeting, and scheduled retrieval, with 4,000 free API credits to test its search capabilities before committing to a paid plan. 

This guide breaks down coverage, fields, pricing, agent tooling, and migration, so you can choose a Serper.dev alternative on evidence or confirm that Serper already fits.

SERPHouse vs Serper.dev: Verdict by Use Case

Serper.dev fits Google-only workflows that value speed and prepaid credits. SERPHouse fits multi-engine collection with device, city, and scheduled retrieval. Your workload decides the better Serper alternative.

Each provider wins a clear set of jobs in the Serper vs SERPHouse matchup. Teams searching for a Serper.dev alternative usually hit one of three walls: Bing coverage, device data, or batch scheduling. 

If none of those walls applies, staying on Serper beats any Serper alternative on cost. Each provider faced the six tests we use for any Serper alternative: engine coverage, result fields, location and device targeting, integration guides, rate limits, and pricing. Prices come from both official pricing pages, checked October 21, 2026.

My take: treat a Serper alternative as a data format decision first and a price decision second. Parsing logic outlives every pricing change. Coverage is the first filter.

Search Engine Coverage and SERP Result Types

Serper.dev covers Google only, across ten search types. SERPHouse covers Google, Bing, and Yahoo, with extra Google endpoints for jobs, forums, local results, and Top 100 pages.

Engines and Endpoints

Endpoint lists show the clearest split between the two providers. Serper’s types appear on its official site, and SERPHouse lists its endpoints in its Google API docs.

Search engines: Serper.dev supports Google, while SERPHouse supports Google, Bing, and Yahoo.

Web search: Serper.dev offers web search, while SERPHouse provides both full and lite web search options.

News, images, videos, and shopping: Both Serper.dev and SERPHouse support these search categories.

Maps and places: Serper.dev supports Maps and places, while SERPHouse offers local search and Place Details.

Scholar and patents: Serper.dev supports Scholar and patent searches, while these capabilities are not listed for SERPHouse.

Jobs, forums, and short videos: SERPHouse supports these search categories, while they are not listed for Serper.dev.

Autocomplete: Both Serper.dev and SERPHouse support autocomplete.

Top 100 results in one call: SERPHouse offers a dedicated endpoint for retrieving the top 100 results in one call, while this capability is not listed for Serper.dev.

“Not listed” means the feature was missing from the official pages we checked. Scholar and Patents give Serper a real edge for research agents. Jobs, forums, and Top 100 give SERPHouse the edge for SEO and data teams, and Bing plus Yahoo in one account make it the direct Serper alternative for mixed engine work.

Targeting Options

Device targeting is where the two providers differ most for rank tracking. Serper’s FAQ lists country and language targeting. SERPHouse adds a desktop or mobile field, a Google domain field, and canonical city names from its locations list.

Any Serper.dev review that skips device targeting misses the gap that matters most, because mobile and desktop SERPs often rank pages in a different order. That device field alone moves many local SEO teams to a Serper.dev alternative.

Supported Types vs Returned Fields

A supported result type appears only when Google shows it for that query. AI Overviews, People Also Ask, and local packs come and go between searches. Run your own keywords through both APIs before you commit to a Serper alternative. Field names decide the next layer of work.

Response Fields: JSON Structure Compared

Both APIs return title, link, snippet, and position for organic results. Serper uses flat camelCase fields, while SERPHouse nests results and adds a full record of each request.

Field by Field

Core organic fields match closely, so most mapping work for a Serper alternative happens on rich SERP blocks. This table compares the samples published by each provider.

Serper places organic results, People Also Ask, and related searches side by side at the top level. That flat layout reads fast and keeps token counts low when an agent reads raw output.

SERPHouse places two records at the top: search_metadata with the request ID, status, and timestamp, and search_parameters with the query, language, location, device, and final Google URL. Organic listings and rich blocks sit one level down under results. For a rank-tracking Serper alternative, that request record is the deciding detail.

In Serper vs SERPHouse terms, Serper reads lighter, and SERPHouse audits better. The echoed parameters let ranking pipelines prove which location and device produced each position.

Agents break on surprises. A tool that returns sitelinks on one call and drops them on the next forces defensive prompt logic. Convert both providers into one internal format at the edge, and switching to a Serper alternative touches a single mapping layer. Price is where the two models split hardest.

Pricing Models and Cost at Scale

Both bill different units, so a fair Serper alternative comparison matches one standard Google page on each side.

SERPHouse counts 10 credits per Top 10 request and 100 per Top 100 request. That gives Basic about 40,000 standard requests and Regular about 80,000. 

Serper caps queries per second, while SERPHouse lists 60 concurrent requests and 60 requests per minute, so these figures measure different things. Serper API pricing uses top-up packs with no subscription.

Expiry Changes the Math

Serper credits expire six months after purchase, so burn speed sets your real rate. Rows assume 1 Serper credit and 10 SERPHouse credits per query.

10,000 monthly Google queries: Serper.dev’s $50 Starter plan, spread over five months, costs $10 per month. SERPHouse’s Basic plan, using 100,000 credits, costs $29.99 per month.

100,000 monthly Google queries: Serper.dev’s $375 Standard plan, spread over five months, costs $75 per month. SERPHouse’s 1,000,000-credit plan, above the Regular tier, requires a custom quote.

100,000 monthly Google queries (Scale plan): Serper.dev’s $1,250 Scale plan costs approximately $208.33 per month when spread over five months, with 600,000 queries used before expiry. SERPHouse’s equivalent 1,000,000-credit option requires a custom quote.

The Scale pack would take 25 months to use at 100,000 a month. A lower sticker price never guarantees an affordable Serper alternative, because expiry moves the effective rate. Serper API pricing rewards big packs only when you burn them inside six months.

In Serper vs SERPHouse cost terms, Serper wins at 10,000 queries. At 100,000, weigh Serper’s $75 against a SERPHouse quote. SERPHouse’s fixed monthly allowance makes it a predictable Serper alternative for steady pipelines. Agent workloads add one more test.

AI Agent and LLM Integrations

Both APIs work as LLM tools through a REST call. SERPHouse adds scheduled jobs, webhooks, an MCP server, and more framework guides, while Serper keeps calls fast and simple.

Calling the APIs

Both providers accept a JSON POST request. Serper authenticates with an API key header and SERPHouse with a Bearer token. Serper answers in 1 to 2 seconds by its own figures. SERPHouse runs a live API over GET or POST, plus a scheduled API with task IDs and webhooks.

Async support is the biggest functional gap for any Serper alternative aimed at batch agents.

Framework Support

More official guides shorten setup when your Serper alternative must join an existing agent stack.

LangGraph works with either provider, since each tool wraps one HTTP call. Teams looking for a Serper for LangChain alternative swap the tool and keep the same agent graph.

Choose by Workload

Pick by integration effort and workload. An LLM can call any SERP API. A chat agent answering one question needs fast synchronous results. An agent refreshing 50,000 rankings overnight needs a queue and webhooks, and that split decides your Serper alternative for agent work.

A practical Serper.dev review scores retries too. Serper notes that a retried request can take 2 to 4 seconds.

Trim responses to title, link, snippet, and position before they reach the model to save tokens. For agent builders, a Serper.dev alternative earns its place through async jobs and an MCP server. Some teams still belong on Serper.

When SERPHouse Is the Better Choice

SERPHouse wins for workloads that need multi-engine coverage, precise device and location targeting, and scheduled retrieval alongside Google search results.

Scheduled batch retrieval suits rank tracking and reporting pipelines that run overnight or at fixed intervals. Bing and Yahoo coverage helps teams diversify beyond Google, while device and city-level targeting supports localized SEO analysis and search intelligence.

Teams arriving from a Serper vs SerpAPI comparison often start with price, but broader coverage can matter more as requirements grow. SERPHouse becomes a stronger Serper alternative when additional engines, targeting options, or batch workflows justify the migration.

A fair SERPHouse review also considers the trade-offs. Teams running only Google queries may not need these extra capabilities, and migration requires testing response formats, updating integrations, and validating output consistency. Switching pays off when the added features solve real workflow gaps.

For Google-only workloads, compare actual query costs before switching. When broader engine coverage, device-level data, or scheduled batches fit your roadmap, plan the migration in steps.

Migration Plan: Switching Between Providers

Switching providers means new endpoints, request bodies, and auth headers. Map the fields, convert both responses into one format, and run both APIs side by side before cutover.

Map the Fields

Most request fields map one to one, which keeps a Serper alternative migration short. Location and device need the most attention.

Run the Switch in Four Steps

1. Build one wrapper per provider. Each wrapper sends the request and returns position, title, URL, and snippet, so every Serper alternative speaks your shared format.
2. Handle two error types. Catch HTTP failures, and also check the response status, since SERPHouse can return an error inside a successful HTTP response.
3. Keep rich blocks raw. Store knowledgeGraph or ai_overview in a separate field for later parsing.
4. Tag every row with its provider. Audits then show which Serper alternative produced each result.

Before You Switch

Run this checklist on your own keywords:

• Test the same query, language, city, and device on both APIs, then compare positions side by side
• Price standard and Top 100 requests separately, with expiry and monthly allowances included
• Check empty results and provider specific blocks for a full week before you trust a new Serper alternative

A week of parallel runs gives you the evidence to move production traffic to a Serper.dev alternative safely.

SERPHouse suits teams needing Google, Bing, and Yahoo results, diverse SERP types, location-aware data, and live or scheduled retrieval, with plans.

For SEO platforms, data pipelines, and AI agents, its SDKs and MCP server offer integration flexibility. Compare pricing and test queries through the pricing page and API documentation.

Conclusion 

Choose Serper.dev when Google only coverage, prepaid credits, and high throughput fit your workload. Pick SERPHouse when multi-engine access, specialized result types, or scheduled retrieval match your architecture.

Base the Serper vs SERPHouse decision on current prices, rate limits, and fields tested on your own queries. The right Serper alternative delivers the SERP data you need at a predictable total cost with the least maintenance.

Testing a Serper alternative on your own keywords takes one afternoon. Want both compared on your keyword set? Let’s run it together on SERPHouse.