Reference example
# Fixed reference example. Playground inputs do not update this sample.
curl --request POST \
--url https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '[
{
"keyword": "logitech",
"internal_list_limit": 1
}
]'curl --request POST \
--url https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
[
{
"keyword": "logitech",
"internal_list_limit": 1
}
]
'import requests
url = "https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live"
payload = [
{
"keyword": "logitech",
"internal_list_limit": 1
}
]
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([{keyword: 'logitech', internal_list_limit: 1}])
};
fetch('https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live', 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/content_analysis/sentiment_analysis/live",
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([
[
'keyword' => 'logitech',
'internal_list_limit' => 1
]
]),
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/content_analysis/sentiment_analysis/live"
payload := strings.NewReader("[\n {\n \"keyword\": \"logitech\",\n \"internal_list_limit\": 1\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/content_analysis/sentiment_analysis/live")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("[\n {\n \"keyword\": \"logitech\",\n \"internal_list_limit\": 1\n }\n]")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live")
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 \"keyword\": \"logitech\",\n \"internal_list_limit\": 1\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": [
{
"type": "<string>",
"positive_connotation_distribution": {
"positive": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"negative": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"neutral": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
}
},
"sentiment_connotation_distribution": {
"anger": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"happiness": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"love": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"sadness": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"share": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"fun": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
}
}
}
]
}
]
}Content Analysis
Content Analysis – Sentiment Analysis API
Content Analysis – Sentiment Analysis API
POST
https://api.aisa.one
/
apis
/
v1
/
dataforseo
/
content_analysis
/
sentiment_analysis
/
live
Reference example
# Fixed reference example. Playground inputs do not update this sample.
curl --request POST \
--url https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '[
{
"keyword": "logitech",
"internal_list_limit": 1
}
]'curl --request POST \
--url https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
[
{
"keyword": "logitech",
"internal_list_limit": 1
}
]
'import requests
url = "https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live"
payload = [
{
"keyword": "logitech",
"internal_list_limit": 1
}
]
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([{keyword: 'logitech', internal_list_limit: 1}])
};
fetch('https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live', 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/content_analysis/sentiment_analysis/live",
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([
[
'keyword' => 'logitech',
'internal_list_limit' => 1
]
]),
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/content_analysis/sentiment_analysis/live"
payload := strings.NewReader("[\n {\n \"keyword\": \"logitech\",\n \"internal_list_limit\": 1\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/content_analysis/sentiment_analysis/live")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("[\n {\n \"keyword\": \"logitech\",\n \"internal_list_limit\": 1\n }\n]")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live")
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 \"keyword\": \"logitech\",\n \"internal_list_limit\": 1\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": [
{
"type": "<string>",
"positive_connotation_distribution": {
"positive": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"negative": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"neutral": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
}
},
"sentiment_connotation_distribution": {
"anger": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"happiness": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"love": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"sadness": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"share": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"fun": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
}
}
}
]
}
]
}Sentiment distributions for the citations of a keyword:
Set this endpoint up in your agent →
positive_connotation_distribution (positive, negative, neutral) and sentiment_connotation_distribution (anger, happiness, love, sadness, share, fun). positive_connotation_threshold and sentiments_connotation_threshold set how confident a classification must be to count. Measured at 5.7 KB. Every response wraps its payload in DataForSEO’s envelope - tasks[0].result holds the data. ⚠️ Both blocks are already inside post_dataforseo_content_summary_live, which costs the same and adds domains, categories, countries and languages - prefer it unless the smaller response matters. To see the sentiment split by star rating use post_dataforseo_content_rating_distribution_live.
Example
curl -X POST "https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '[{"keyword": "...", "keyword_fields": "...", "page_type": "..."}]'
// Copy this whole block into Claude Code, Codex, Cursor or any coding agent.
// It carries everything needed to connect, authorize and run this example —
// no key to paste, one click of Allow in the browser.
{
"operation_id": "post_dataforseo_content_sentiment_analysis_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/api-reference/dataforseo/post_dataforseo-content-analysis-sentiment-analysis-live.md
// Then run the call and show me the result.
First time? Point any MCP client at
https://mcp.aisa.one/mcp — Claude
Code, Codex, Cursor, VS Code and the rest. Authorization is OAuth: the client
opens a browser, you click Allow once, and there is no key to paste. The
commands per client, and what each call costs, are on
aisa.one/mcp.Cost and request rules
Published reference values are not an account-specific quote or a settled charge. For endpoints supporting X-AISA-Cost-Mode: quote, obtain a free quote for your exact request before execution; reconcile the settled cost with response metadata and Usage Logs. USD amounts use 1,000,000 integer micro-USD per dollar.- Default request reference estimate (USD): 0.024
- Cost contract: response_usd
- Published reference multiplier: 1.0
- Settlement evidence source: response_body
Authorizations
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Body
application/json
target keyword required field UTF-8 encoding the keywords will be converted to a lowercase format; Note: to match an exact phrase instead of a stand-alone keyword, use double quotes and backslashes; example: "keyword": ""tesla palo alto"" learn more about rules and limitations of keyword and keywords fields in DataForSEO APIs in this Help Center article
target keyword fields and target keywords optional field use this parameter to filter the dataset by keywords that certain fields should contain; fields you can specify: title, main_title, previous_title, snippet you can indicate several fields; Note: to match an exact phrase instead of a stand-alone keyword, use double quotes and backslashes; example: "keyword_fields": { "snippet": ""logitech mouse"", "main_title": "sale" }
Show child attributes
Show child attributes
target page types optional field use this parameter to filter the dataset by page types possible values: "ecommerce", "news", "blogs", "message-boards", "organization"
maximum number of elements within internal arrays optional field you can use this field to limit the number of elements within the following arrays: top_domains text_categories page_categories countries languages default value: 1 maximum value: 20
positive connotation threshold optional field specified as the probability index threshold for positive sentiment related to the citation content if you specify this field, connotation_types object in the response will only contain data on citations with positive sentiment probability more than or equal to the specified value possible values: from 0 to 1 default value: 0.4
sentiment connotation threshold optional field specified as the probability index threshold for sentiment connotations related to the citation content if you specify this field, sentiment_connotations object in the response will only contain data on citations where the probability per each sentiment is more than or equal to the specified value possible values: from 0 to 1 default value: 0.4
initial dataset filtering parameters optional field initial filtering parameters that apply to fields in the Search endpoint you can add several filters at once (8 filters maximum) you should set a logical operator and, or between the conditions the following operators are supported: regex, not_regex, <, <=, >, >=, =, <>, in, not_in, like,not_like, has, has_not, match, not_match you can use the % operator with like and not_like to match any string of zero or more characters example: ["domain","<>", "logitech.com"] [["domain","<>","logitech.com"],"and",["content_info.connotation_types.negative",">",1000]] [["domain","<>","logitech.com"]], "and", [["content_info.connotation_types.negative",">",1000], "or", ["content_info.text_category","has",10994]]] for more information about filters, please refer to Content Analysis API – Filters learn more about the initial dataset filters in this help center article.
defines the scale used for calculating and displaying the rank values optional field you can use this parameter to choose whether rank values are presented on a 0–100 or 0–1000 scale possible values: one_hundred — rank values are displayed on a 0–100 scale one_thousand — rank values are displayed on a 0–1000 scale default value: one_thousand learn more about how this parameter works in this Help Center article
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
Example:
[
{
"keyword": "logitech",
"internal_list_limit": 1
}
]
Response
object | null
Successful operation
the current version of the API
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
total tasks cost, USD
the number of tasks in the tasks array
the number of tasks in the tasks array returned with an error
array of tasks
Show child attributes
Show child attributes