Output formats

Get Google results as full JSON, token-lean compact JSON or LLM-ready Markdown, and cut them down further with fields projection. X-Tokens-Estimate tells you the size.

View as Markdown

Every search endpoint can answer in three formats. They contain the same search, just packaged for different consumers, and they cost the same credits.

`format`	Content type	Best for
`json` (default)	`application/json`	Apps and pipelines that parse specific fields. The full `request` / `results` / `meta` envelope.
`compact`	`application/json`	Agents that want structure but few tokens. The same `results`, trimmed: short snippets, no thumbnails, positions or tracking data.
`markdown` (alias `md`)	`text/markdown`	Putting results straight into an LLM prompt or a tool result.

JSON-only endpoints

/v1/autocomplete and /v1/lens always return JSON; their responses are already small. format: "compact" still works there.

JSON

The default. Every endpoint returns the same envelope, with snake_case keys throughout:

request: the normalised request that ran, with defaults filled in (endpoint, engine, q, country, language, num, page, device…).
results: the endpoint’s main list. Organic results on /v1/search, articles on /v1/news, places on /v1/maps, reviews on /v1/reviews, suggestions on /v1/autocomplete, and so on. /v1/webpage is the only endpoint without results; it returns url, markdown and metadata.
Endpoint extras. On /v1/search: related_searches (always present), and answer_box, knowledge_graph, people_also_ask, top_stories, places and ads when Google shows them.
meta: request_id, credits_used, cached, engine (the provider that answered), route, latency_ms, parse_quality and resolved_urls.

Every link is the resolved destination URL and every result carries a canonical domain.

format=json · illustrative

{
  "request": {
    "endpoint": "search",
    "engine": "google",
    "q": "best espresso machine 2026",
    "country": "us",
    "language": "en",
    "num": 10,
    "page": 1,
    "device": "desktop",
    "autocorrect": true
  },
  "results": [
    {
      "position": 1,
      "title": "The Best Espresso Machines of 2026, Tested and Reviewed",
      "link": "https://www.example.com/best-espresso-machines",
      "domain": "example.com",
      "displayed_link": "https://www.example.com › best-espresso-machines",
      "snippet": "We pulled more than 1,200 shots on 42 machines to find the best espresso makers for every budget, from beginner-friendly to prosumer.",
      "date": "Sep 12, 2026",
      "sitelinks": [
        {
          "title": "Best budget pick",
          "link": "https://www.example.com/best-espresso-machines#budget"
        },
        {
          "title": "Best dual boiler",
          "link": "https://www.example.com/best-espresso-machines#dual-boiler"
        }
      ]
    },
    {
      "position": 2,
      "title": "Espresso Machine Buying Guide (2026)",
      "link": "https://coffee.example.org/guides/espresso",
      "domain": "coffee.example.org",
      "displayed_link": "https://coffee.example.org › guides › espresso",
      "snippet": "Single boiler, heat exchanger or dual boiler? What the specs mean and which features are worth paying for."
    },
    {
      "position": 3,
      "title": "r/espresso: What machine would you buy in 2026?",
      "link": "https://www.reddit.com/r/espresso/comments/abc123/",
      "domain": "reddit.com",
      "displayed_link": "https://www.reddit.com › r › espresso",
      "snippet": "Discussion thread with 480 comments comparing entry-level and prosumer machines."
    }
  ],
  "people_also_ask": [
    {
      "question": "What is the #1 rated espresso machine?",
      "snippet": "Reviewers most often rank dual-boiler machines with PID control at the top…",
      "link": "https://www.example.com/best-espresso-machines"
    },
    {
      "question": "Is a $500 espresso machine worth it?",
      "snippet": "For daily drinkers, a mid-range machine usually pays for itself within a year…",
      "link": "https://coffee.example.org/guides/espresso"
    }
  ],
  "related_searches": [
    {
      "query": "best espresso machine under $500"
    },
    {
      "query": "best espresso machine for beginners"
    },
    {
      "query": "dual boiler vs heat exchanger"
    }
  ],
  "meta": {
    "request_id": "req_01J8ZK4M6Q2V7",
    "credits_used": 1,
    "cached": false,
    "engine": "google",
    "latency_ms": 942,
    "parse_quality": "ok",
    "resolved_urls": true
  }
}

The fields of each endpoint are documented on its page, for example Search.

Compact

format: "compact" returns a token-lean JSON object with only what a model needs to reason about the results. It keeps the same results key and snake_case names, shortens snippets, drops empty values, and removes positions, thumbnails, sitelinks and tracking data. meta stays, and fields works on compact output too.

cURL

TypeScript

Python

curl https://api.serpkite.com/v1/search \
  -H "Authorization: Bearer $SERPKITE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"q":"best espresso machine 2026","country":"us","format":"compact"}'

format=compact · illustrative

{
  "results": [
    {
      "title": "The Best Espresso Machines of 2026, Tested and Reviewed",
      "link": "https://www.example.com/best-espresso-machines",
      "snippet": "We pulled more than 1,200 shots on 42 machines to find the best espresso makers for every budget, from beginner-friendly to prosumer.",
      "date": "Sep 12, 2026"
    },
    {
      "title": "Espresso Machine Buying Guide (2026)",
      "link": "https://coffee.example.org/guides/espresso",
      "snippet": "Single boiler, heat exchanger or dual boiler? What the specs mean and which features are worth paying for."
    },
    {
      "title": "r/espresso: What machine would you buy in 2026?",
      "link": "https://www.reddit.com/r/espresso/comments/abc123/",
      "snippet": "Discussion thread with 480 comments comparing entry-level and prosumer machines."
    }
  ],
  "people_also_ask": [
    "What is the #1 rated espresso machine?",
    "Is a $500 espresso machine worth it?"
  ],
  "meta": {
    "request_id": "req_01J8ZK4M6Q2V7",
    "credits_used": 1,
    "cached": false,
    "engine": "google",
    "latency_ms": 942,
    "parse_quality": "ok",
    "resolved_urls": true
  }
}

Compact keys per endpoint:

Endpoint	Keys
`/v1/search`, `/v1/scholar`, `/v1/patents`, `/v1/lens`	`results[]` (`title`, `link`, `snippet`, `date`, `content`, `cited_by`, `year`), plus on /v1/search `answer`, `knowledge_graph` (`title`, `type`, `description`, `website`), `people_also_ask[]` (question strings), `top_stories[]`
`/v1/news`	`results[]` (`title`, `link`, `source`, `date`, `snippet`)
`/v1/images`	`results[]` (`title`, `image_url`, `link`)
`/v1/videos`	`results[]` (`title`, `link`, `channel`, `duration`, `date`)
`/v1/maps`, `/v1/places`	`results[]` (`title`, `address`, `rating`, `rating_count`, `phone`, `website`, `type`)
`/v1/reviews`	`results[]` (`rating`, `date`, `text`)
`/v1/shopping`	`results[]` (`title`, `price`, `source`, `link`, `rating`)
`/v1/autocomplete`	`results[]` (suggestion strings)
`/v1/webpage`	`url`, `title`, `markdown`

Keys other than results only appear when Google returned something for them, so check for presence rather than null.

Markdown

format: "markdown" renders the results page as a Markdown document with Content-Type: text/markdown. Headings separate the sections (results, People also ask, related searches) and links are kept. It is usually the cheapest way to give a model the whole page.

cURL

TypeScript

Python

curl https://api.serpkite.com/v1/search \
  -H "Authorization: Bearer $SERPKITE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"q":"best espresso machine 2026","country":"us","format":"markdown"}'

format=markdown · illustrative

# best espresso machine 2026

## Results
1. **The Best Espresso Machines of 2026, Tested and Reviewed** — example.com
   https://www.example.com/best-espresso-machines
   We pulled more than 1,200 shots on 42 machines to find the best espresso makers for every budget.
2. **Espresso Machine Buying Guide (2026)** — coffee.example.org
   https://coffee.example.org/guides/espresso
   Single boiler, heat exchanger or dual boiler? What the specs mean.
3. **r/espresso: What machine would you buy in 2026?** — reddit.com
   https://www.reddit.com/r/espresso/comments/abc123/

## People also ask
- **What is the #1 rated espresso machine?** Reviewers most often rank dual-boiler machines with PID control at the top…
- **Is a $500 espresso machine worth it?** For daily drinkers, a mid-range machine usually pays for itself within a year…

## Related searches
best espresso machine under $500 · best espresso machine for beginners · dual boiler vs heat exchanger

The body is plain text. The SDKs return it as a string (SearchMarkdown in Go); with a raw HTTP client read it with res.text() (Node) or res.text (Python), not as JSON. Errors are still JSON with the usual error shape, so check the status code first.

Fields projection

fields keeps only the parts of the response you ask for. It takes a comma-separated list of dot paths. Arrays are traversed element by element, so results.title keeps the title of every result.

cURL

TypeScript

Python

curl https://api.serpkite.com/v1/search \
  -H "Authorization: Bearer $SERPKITE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"q":"best espresso machine 2026","fields":"results.title,results.link,knowledge_graph.title"}'

{
  "request": { "endpoint": "search", "engine": "google", "q": "best espresso machine 2026", "country": "us", "language": "en", "num": 10, "page": 1 },
  "results": [
    { "title": "The Best Espresso Machines of 2026, Tested and Reviewed", "link": "https://www.example.com/best-espresso-machines" },
    { "title": "Espresso Machine Buying Guide (2026)", "link": "https://coffee.example.org/guides/espresso" }
  ],
  "knowledge_graph": { "title": "Espresso machine" },
  "meta": { "request_id": "req_01J8ZK4M6Q2V7", "credits_used": 1, "cached": false, "engine": "google" }
}

Rules:

Up to 50 paths per request, each at most 4 levels deep (results.sitelinks.title is fine).
request and meta are always kept, so you can still read the request ID and cost.
Paths that don’t exist in the response are ignored.
With format: "markdown", top-level names in fields select which sections are rendered, e.g. fields: "answer_box,results" drops People also ask and related searches.
Invalid paths (empty segments, too deep, too many) return 400 invalid_request.

Measuring size: X-Tokens-Estimate

Every response carries X-Tokens-Estimate, an approximation of the LLM tokens in the body (characters divided by four). Use it to compare formats for your queries, or to decide how many results fit in a context window before you read the body.

curl -s -o /dev/null -D - https://api.serpkite.com/v1/search \
  -H "Authorization: Bearer $SERPKITE_API_KEY" -H "Content-Type: application/json" \
  -d '{"q":"best espresso machine 2026","format":"markdown"}' | grep -i x-tokens-estimate

It is an estimate, not your model’s tokenizer; real counts vary by model and language. For a side-by-side comparison on your own query, try the SERP token counter.

Choosing a format

Building an app or storing results: json, with fields to drop what you don’t read.
Agent tool results where the model reasons over the page: markdown.
Agent tool results where your code post-processes before the model sees them: compact.
Feeding full pages, not just snippets: add include_content.

Last updated: 2026-09-29