List answers

curl -X POST https://api.rankraft.ai/v1/answers \
  -H "X-API-Key: $RANKRAFT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "site_id": "3f2c9a10-7b1e-4c55-9d2a-1a2b3c4d5e6f",
    "start_date": "2026-09-24",
    "end_date": "2026-09-30",
    "platforms": ["chatgpt"],
    "include": ["prompt", "platform", "date", "text", "mentions", "citations"],
    "limit": 10
  }'

// npm install rankraft-js · https://www.npmjs.com/package/rankraft-js
import { RankRaft } from "rankraft-js";

const rr = new RankRaft(); // reads RANKRAFT_API_KEY

const answers = rr.answers.query({
  site_id: "3f2c9a10-7b1e-4c55-9d2a-1a2b3c4d5e6f",
  start_date: "2026-09-24",
  end_date: "2026-09-30",
  platforms: ["chatgpt"],
  include: ["prompt", "platform", "date", "text", "mentions", "citations"],
  limit: 10,
});
for await (const a of answers) console.log(a.date, a.prompt?.text, a.mentions);

# pip install rankraft-py · https://pypi.org/project/rankraft-py/
from rankraft import RankRaft

with RankRaft() as rr:  # reads RANKRAFT_API_KEY
    page = rr.answers.query(
        site_id="3f2c9a10-7b1e-4c55-9d2a-1a2b3c4d5e6f",
        start_date="2026-09-24",
        end_date="2026-09-30",
        platforms=["chatgpt"],
        include=["prompt", "platform", "date", "text", "mentions", "citations"],
        limit=10,
    )
    for a in page.auto_paging():
        print(a["date"], a["prompt"]["text"], a["mentions"])

{
  "info": {
    "site_id": "3f2c9a10-7b1e-4c55-9d2a-1a2b3c4d5e6f",
    "start_date": "2026-09-24",
    "end_date": "2026-09-30",
    "count": 1,
    "total_results": 7,
    "next_cursor": "eyJvIjox…"
  },
  "data": [
    {
      "id": "a9d3c1e2-4b5f-4a6e-8c7d-9e0f1a2b3c4d",
      "date": "2026-09-30",
      "platform": "chatgpt",
      "prompt": {
        "id": "8a1e4b2c-6d0f-4e3a-9b51-2c7d8e9f0a1b",
        "text": "best mixed pickle brand"
      },
      "text": "For mixed pickle, Shan Foods and Misali Foods are the most recommended…",
      "mentions": ["Shan Foods", "Misali Foods"],
      "citations": [
        {
          "url": "https://www.daraz.pk/products/mixed-achar",
          "domain": "daraz.pk",
          "title": "Mixed Achar 1kg",
          "position": 1,
          "own_site": false
        }
      ]
    }
  ]
}

curl -X POST https://api.rankraft.ai/v1/answers \
  -H "X-API-Key: $RANKRAFT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "site_id": "3f2c9a10-7b1e-4c55-9d2a-1a2b3c4d5e6f",
    "start_date": "2026-09-24",
    "end_date": "2026-09-30",
    "platforms": ["chatgpt"],
    "include": ["prompt", "platform", "date", "text", "mentions", "citations"],
    "limit": 10
  }'

// npm install rankraft-js · https://www.npmjs.com/package/rankraft-js
import { RankRaft } from "rankraft-js";

const rr = new RankRaft(); // reads RANKRAFT_API_KEY

const answers = rr.answers.query({
  site_id: "3f2c9a10-7b1e-4c55-9d2a-1a2b3c4d5e6f",
  start_date: "2026-09-24",
  end_date: "2026-09-30",
  platforms: ["chatgpt"],
  include: ["prompt", "platform", "date", "text", "mentions", "citations"],
  limit: 10,
});
for await (const a of answers) console.log(a.date, a.prompt?.text, a.mentions);

# pip install rankraft-py · https://pypi.org/project/rankraft-py/
from rankraft import RankRaft

with RankRaft() as rr:  # reads RANKRAFT_API_KEY
    page = rr.answers.query(
        site_id="3f2c9a10-7b1e-4c55-9d2a-1a2b3c4d5e6f",
        start_date="2026-09-24",
        end_date="2026-09-30",
        platforms=["chatgpt"],
        include=["prompt", "platform", "date", "text", "mentions", "citations"],
        limit=10,
    )
    for a in page.auto_paging():
        print(a["date"], a["prompt"]["text"], a["mentions"])

{
  "info": {
    "site_id": "3f2c9a10-7b1e-4c55-9d2a-1a2b3c4d5e6f",
    "start_date": "2026-09-24",
    "end_date": "2026-09-30",
    "count": 1,
    "total_results": 7,
    "next_cursor": "eyJvIjox…"
  },
  "data": [
    {
      "id": "a9d3c1e2-4b5f-4a6e-8c7d-9e0f1a2b3c4d",
      "date": "2026-09-30",
      "platform": "chatgpt",
      "prompt": {
        "id": "8a1e4b2c-6d0f-4e3a-9b51-2c7d8e9f0a1b",
        "text": "best mixed pickle brand"
      },
      "text": "For mixed pickle, Shan Foods and Misali Foods are the most recommended…",
      "mentions": ["Shan Foods", "Misali Foods"],
      "citations": [
        {
          "url": "https://www.daraz.pk/products/mixed-achar",
          "domain": "daraz.pk",
          "title": "Mixed Achar 1kg",
          "position": 1,
          "own_site": false
        }
      ]
    }
  ]
}

The stored answers themselves, newest first: the text exactly as each engine returned it, the brands it named and the sources it cited. Pages are small (at most 50) because answers are long.

Body

string

required

The site’s id, from List sites.

string

required

Inclusive day, YYYY-MM-DD, UTC.

string

required

Inclusive day, YYYY-MM-DD, UTC. At most 92 days after start_date.

enum<string>[]

Any of: ai_overviews, ai_mode, chatgpt, gemini, claude, perplexity, copilot.

string[]

Up to 100 prompt ids.

enum<string>[]

Any of: prompt, platform, date, text, brand_mentioned, brand_position, sentiment, mentions, citations. Leave out text for much smaller responses.

integer

default:20

Rows per page, 1–50.

string

Opaque cursor from info.next_cursor.

Response

object

Show properties

integer

Rows in this page.

integer

Rows across all pages.

string

Pass as cursor for the next page; null on the last page.

string

object[]

Show properties

string

object

Show properties

string

The answer exactly as the engine returned it.

boolean

number

Order of your brand’s first mention (1 = first), or null.

string

positive, neutral, negative, or null when not judged.

string[]

Brands named, in order of first appearance.

object[]

Show properties

string

number

Order among the answer’s sources (1 = first).

boolean

curl -X POST https://api.rankraft.ai/v1/answers \
  -H "X-API-Key: $RANKRAFT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "site_id": "3f2c9a10-7b1e-4c55-9d2a-1a2b3c4d5e6f",
    "start_date": "2026-09-24",
    "end_date": "2026-09-30",
    "platforms": ["chatgpt"],
    "include": ["prompt", "platform", "date", "text", "mentions", "citations"],
    "limit": 10
  }'

// npm install rankraft-js · https://www.npmjs.com/package/rankraft-js
import { RankRaft } from "rankraft-js";

const rr = new RankRaft(); // reads RANKRAFT_API_KEY

const answers = rr.answers.query({
  site_id: "3f2c9a10-7b1e-4c55-9d2a-1a2b3c4d5e6f",
  start_date: "2026-09-24",
  end_date: "2026-09-30",
  platforms: ["chatgpt"],
  include: ["prompt", "platform", "date", "text", "mentions", "citations"],
  limit: 10,
});
for await (const a of answers) console.log(a.date, a.prompt?.text, a.mentions);

# pip install rankraft-py · https://pypi.org/project/rankraft-py/
from rankraft import RankRaft

with RankRaft() as rr:  # reads RANKRAFT_API_KEY
    page = rr.answers.query(
        site_id="3f2c9a10-7b1e-4c55-9d2a-1a2b3c4d5e6f",
        start_date="2026-09-24",
        end_date="2026-09-30",
        platforms=["chatgpt"],
        include=["prompt", "platform", "date", "text", "mentions", "citations"],
        limit=10,
    )
    for a in page.auto_paging():
        print(a["date"], a["prompt"]["text"], a["mentions"])

{
  "info": {
    "site_id": "3f2c9a10-7b1e-4c55-9d2a-1a2b3c4d5e6f",
    "start_date": "2026-09-24",
    "end_date": "2026-09-30",
    "count": 1,
    "total_results": 7,
    "next_cursor": "eyJvIjox…"
  },
  "data": [
    {
      "id": "a9d3c1e2-4b5f-4a6e-8c7d-9e0f1a2b3c4d",
      "date": "2026-09-30",
      "platform": "chatgpt",
      "prompt": {
        "id": "8a1e4b2c-6d0f-4e3a-9b51-2c7d8e9f0a1b",
        "text": "best mixed pickle brand"
      },
      "text": "For mixed pickle, Shan Foods and Misali Foods are the most recommended…",
      "mentions": ["Shan Foods", "Misali Foods"],
      "citations": [
        {
          "url": "https://www.daraz.pk/products/mixed-achar",
          "domain": "daraz.pk",
          "title": "Mixed Achar 1kg",
          "position": 1,
          "own_site": false
        }
      ]
    }
  ]
}

Get started

Discovery

Prompts

Reports

Agent Analytics

Action Center

Body

Response

​Body

​Response

Body

Response