curl --request POST \
--url https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
[
{
"language_code": "en",
"location_code": 2840,
"keyword": "albert einstein"
}
]
'import requests
url = "https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced"
payload = [
{
"language_code": "en",
"location_code": 2840,
"keyword": "albert einstein"
}
]
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify([{language_code: 'en', location_code: 2840, keyword: 'albert einstein'}])
};
fetch('https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
[
'language_code' => 'en',
'location_code' => 2840,
'keyword' => 'albert einstein'
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced"
payload := strings.NewReader("[\n {\n \"language_code\": \"en\",\n \"location_code\": 2840,\n \"keyword\": \"albert einstein\"\n }\n]")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("[\n {\n \"language_code\": \"en\",\n \"location_code\": 2840,\n \"keyword\": \"albert einstein\"\n }\n]")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "[\n {\n \"language_code\": \"en\",\n \"location_code\": 2840,\n \"keyword\": \"albert einstein\"\n }\n]"
response = http.request(request)
puts response.read_body{
"version": "<string>",
"status_code": 123,
"status_message": "<string>",
"time": "<string>",
"cost": 123,
"tasks_count": 123,
"tasks_error": 123,
"tasks": [
{
"id": "<string>",
"status_code": 123,
"status_message": "<string>",
"time": "<string>",
"cost": 123,
"result_count": 123,
"path": [
"<string>"
],
"data": {},
"result": [
{
"keyword": "<string>",
"location_code": 123,
"language_code": "<string>",
"model": "<string>",
"check_url": "<string>",
"datetime": "<string>",
"markdown": "<string>",
"search_results": [
{
"type": "<string>",
"url": "<string>",
"domain": "<string>",
"title": "<string>",
"description": "<string>",
"breadcrumb": "<string>"
}
],
"sources": [
{
"type": "<string>",
"title": "<string>",
"snippet": "<string>",
"domain": "<string>",
"url": "<string>",
"thumbnail": "<string>",
"source_name": "<string>",
"publication_date": "<string>",
"markdown": "<string>"
}
],
"fan_out_queries": [
"<string>"
],
"brand_entities": [
{
"type": "<string>",
"title": "<string>",
"category": "<string>",
"markdown": "<string>",
"urls": {}
}
],
"se_results_count": 123,
"item_types": [
"<string>"
],
"items_count": 123,
"items": [
{
"markdown": "<string>",
"sources": [
{
"type": "<string>",
"title": "<string>",
"snippet": "<string>",
"domain": "<string>",
"url": "<string>",
"thumbnail": "<string>",
"source_name": "<string>",
"publication_date": "<string>",
"markdown": "<string>"
}
],
"brand_entities": [
{
"type": "<string>",
"title": "<string>",
"category": "<string>",
"markdown": "<string>",
"urls": {}
}
],
"type": "<string>",
"rank_group": 123,
"rank_absolute": 123
}
]
}
]
}
]
}实时 ChatGPT LLM 抓取器
像用户那样把 keyword 问给 ChatGPT,返回解析后的答案。
curl --request POST \
--url https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
[
{
"language_code": "en",
"location_code": 2840,
"keyword": "albert einstein"
}
]
'import requests
url = "https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced"
payload = [
{
"language_code": "en",
"location_code": 2840,
"keyword": "albert einstein"
}
]
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify([{language_code: 'en', location_code: 2840, keyword: 'albert einstein'}])
};
fetch('https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
[
'language_code' => 'en',
'location_code' => 2840,
'keyword' => 'albert einstein'
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced"
payload := strings.NewReader("[\n {\n \"language_code\": \"en\",\n \"location_code\": 2840,\n \"keyword\": \"albert einstein\"\n }\n]")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("[\n {\n \"language_code\": \"en\",\n \"location_code\": 2840,\n \"keyword\": \"albert einstein\"\n }\n]")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "[\n {\n \"language_code\": \"en\",\n \"location_code\": 2840,\n \"keyword\": \"albert einstein\"\n }\n]"
response = http.request(request)
puts response.read_body{
"version": "<string>",
"status_code": 123,
"status_message": "<string>",
"time": "<string>",
"cost": 123,
"tasks_count": 123,
"tasks_error": 123,
"tasks": [
{
"id": "<string>",
"status_code": 123,
"status_message": "<string>",
"time": "<string>",
"cost": 123,
"result_count": 123,
"path": [
"<string>"
],
"data": {},
"result": [
{
"keyword": "<string>",
"location_code": 123,
"language_code": "<string>",
"model": "<string>",
"check_url": "<string>",
"datetime": "<string>",
"markdown": "<string>",
"search_results": [
{
"type": "<string>",
"url": "<string>",
"domain": "<string>",
"title": "<string>",
"description": "<string>",
"breadcrumb": "<string>"
}
],
"sources": [
{
"type": "<string>",
"title": "<string>",
"snippet": "<string>",
"domain": "<string>",
"url": "<string>",
"thumbnail": "<string>",
"source_name": "<string>",
"publication_date": "<string>",
"markdown": "<string>"
}
],
"fan_out_queries": [
"<string>"
],
"brand_entities": [
{
"type": "<string>",
"title": "<string>",
"category": "<string>",
"markdown": "<string>",
"urls": {}
}
],
"se_results_count": 123,
"item_types": [
"<string>"
],
"items_count": 123,
"items": [
{
"markdown": "<string>",
"sources": [
{
"type": "<string>",
"title": "<string>",
"snippet": "<string>",
"domain": "<string>",
"url": "<string>",
"thumbnail": "<string>",
"source_name": "<string>",
"publication_date": "<string>",
"markdown": "<string>"
}
],
"brand_entities": [
{
"type": "<string>",
"title": "<string>",
"category": "<string>",
"markdown": "<string>",
"urls": {}
}
],
"type": "<string>",
"rank_group": 123,
"rank_absolute": 123
}
]
}
]
}
]
}keyword 问给 ChatGPT,返回解析后的答案。返回 keyword、location_code、language_code、model、datetime、markdown、sources、fan_out_queries 和 brand_entities——markdown 是助手渲染出的答案,sources 是它引用的页面,brand_entities 是它点到的品牌。 实测 11.3 KB。force_web_search 让它去联网而不是凭训练数据回答。响应包在信封里:数据在 tasks[0].result,成败在 tasks[0].status_code——请求被拒时 HTTP 仍是 200。 这是回答「ChatGPT 怎么说我们」的端点;要跨大量回答统计提及次数,请用 post_dataforseo_ai_llm_mentions_aggregated_metrics_live,别反复抓取。原始形式是 post_dataforseo_ai_chat_gpt_llm_scraper_live_html。
示例
curl -X POST "https://api.aisa.one/apis/v1/dataforseo/ai_optimization/chat_gpt/llm_scraper/live/advanced" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '[{"keyword": "...", "location_name": "...", "location_code": "..."}]'
// 把整段复制给 Claude Code、Codex、Cursor 或任意 coding agent。
// 连接、授权、跑通这个例子需要的东西都在里面 ——
// 不用粘贴任何 key,浏览器里点一次 Allow 就好。
{
"operation_id": "post_dataforseo_ai_chat_gpt_llm_scraper_live",
"arguments": {},
"max_price_usd": 0.05
}
// ── for the agent ─────────────────────────────────────────────────────────
// Register the AIsa MCP server, then call its `use` tool with the JSON above.
// name aisa
// endpoint https://mcp.aisa.one/mcp
// transport streamable-http
// auth OAuth. The server publishes RFC 9728 metadata, so open a
// browser and the user clicks Allow once — nothing to paste.
// If AISA_API_KEY is set, send it as a bearer header instead.
// Use your own MCP mechanism, not a hand-edited config file:
// Codex codex mcp add aisa --url https://mcp.aisa.one/mcp
// Claude Code claude mcp add --transport http -s user aisa https://mcp.aisa.one/mcp
// Cursor / VS Code a "url" entry for https://mcp.aisa.one/mcp in the MCP config
// The server lists five tools over https://mcp.aisa.one/servers worth of APIs:
// search, get_details, use, batch_use, list_categories. search and
// get_details are free; use is billed per call and max_price_usd refuses
// anything above the cap before spending. This operation's full contract —
// every argument, the response shape, the price and the pitfalls — is at
// https://aisa.one/docs/zh/api-reference/dataforseo/post_dataforseo-ai-optimization-chat-gpt-llm-scraper-live-advanced.md
// Then run the call and show me the result.
https://mcp.aisa.one/mcp —— Claude Code、
Codex、Cursor、VS Code 都可以。鉴权走 OAuth:客户端打开浏览器,你点一次
Allow,不需要粘贴任何 key。各客户端的具体命令和每次调用的价格见
aisa.one/zh-cn/mcp。授权
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
请求体
keyword
required field
you can specify up to 2000 characters in the keyword field
all %## will be decoded (plus character ‘+’ will be decoded to a space character)
if you need to use the “%” character for your keyword, please specify it as “%25”;
if you need to use the “+” character for your keyword, please specify it as “%2B”
learn more about rules and limitations of keyword and keywords fields in DataForSEO APIs in this Help Center article
full name of search engine location
required field if you don't specify location_code
if you use this field, you don't need to specify location_code
you can receive the list of available locations of the search engine with their location_name by making a separate request to the https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_scraper/locations
example:United States
search engine location code
required field if you don't specify location_name
if you use this field, you don't need to specify location_name
you can receive the list of available locations of the search engines with their location_code by making a separate request to the https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_scraper/locations
example:2840
full name of search engine language
required field if you don't specify language_code;
if you use this field, you don't need to specify language_code;
you can receive the list of available languages of the search engine with their language_name by making a separate request to the https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_scraper/languages
search engine language code
required field if you don't specify language_name;
if you use this field, you don't need to specify language_name;
you can receive the list of available languages of the search engine with their language_code by making a separate request to the https://api.dataforseo.com/v3/ai_optimization/chat_gpt/llm_scraper/languages
force AI agent to use web search
optional field
when enabled, the AI model is forced to access and cite current web information;
default value: false;
Note: even if the parameter is set to true, there is no guarantee web sources will be cited in the response
user-defined task identifier
optional field
the character limit is 255
you can use this parameter to identify the task and match it with the result
you will find the specified tag value in the data object of the response
[
{
"language_code": "en",
"location_code": 2840,
"keyword": "albert einstein"
}
]
响应
Successful operation
API 的当前版本
general status code you can find the full list of the response codes here
general informational message you can find the full list of general informational messages here
total execution time, seconds
任务总成本(美元)
tasks 数组中的任务数量
返回错误的 tasks 数组中的任务数量
array of tasks
Show child attributes
Show child attributes