如何查小红书蒲公英关键词的搜索指数和关联词

用 2 个接口：小红书蒲公英关联词 → 小红书蒲公英关键词逐日搜索指数。下面的示例一共 3 次调用，合计 $0.12；失败的调用不收费。

从一个词出发，先取它在蒲公英上的关联词，每个带排名和搜索指数；再取原词和挑出的词逐日的搜索指数、笔记数、曝光、阅读和互动。最后得到一张按天排的表，看这几个词在小红书上的热度怎么走。

第 1 步：小红书蒲公英关联词

按一个词取它在蒲公英上的关联词，一次调用全部返回，不用翻页。每条的 keyword 是关联词，rank 是排名，search_index 是这个词的搜索指数，relation 说明是怎么关联上的。挑出要看的词，取它们的 keyword，下一步用。

cURLPythonTypeScript命令行

curl -G "https://api.dataxapi.com/v1/xiaohongshu/pgy/keywords/related" \
  --data-urlencode "keyword=面膜" \
  -H "Authorization: Bearer $DATAXAPI_API_KEY"

# pip install dataxapi
from dataxapi import DataXAPI

dx = DataXAPI()  # reads DATAXAPI_API_KEY
result = dx.xiaohongshu.pgy.keywords.related(keyword="面膜")
print(result["data"]["items"])

// npm i @dataxapi/sdk
import { DataXAPI } from "@dataxapi/sdk";

const dx = new DataXAPI(); // reads DATAXAPI_API_KEY
const result = await dx.xiaohongshu.pgy.keywords.related({ keyword: "面膜" });
console.log(result.data.items);

dataxapi call xiaohongshu.pgy.keywords.related 'keyword=面膜'

录制的返回

{
  "code": "ok",
  "request_id": "14b8ced1-2b33-47f6-90f7-86463f68684e",
  "data": {
    "items": [
      {
        "keyword": "烧烤",
        "related_to": "露营",
        "relation": "prior",
        "rank": 1,
        "search_index": 2638774
      },
      // … 另有 97 条
    ]
  },
  "page": {
    "next_cursor": null,
    "cursor_expires_at": null,
    "has_more": false,
    "returned": 98
  },
  "warnings": [],
  "meta": {
    "capability": "xiaohongshu.pgy.keywords.related",
    "result_status": "complete",
    "fetched_at": "2026-10-12T21:42:15.000Z",
    "cached": false,
    "replayed": false,
    "unavailable": {
      "relevance": "platform",
      "composite_index": "platform"
    },
    "billing": {
      "amount": "0.04",
      "currency": "USD",
      "balance_after": "9.96"
    }
  }
}

取自 2026-10-12 21:42 UTC 录下的真实返回。名字、正文和编号是示例，链接也是，都不是录到的原文（页面不展示任何人的个人信息）；数字是原样。长列表做了截断。请求号、游标和余额是示意。

小红书蒲公英关联词 · $0.0400 / 一次 · 参数、字段和报错见接口页 →

第 2 步：小红书蒲公英关键词逐日搜索指数

一次一个词：把词放进 keyword，返回一条，points 里是逐日的 search_index、notes（笔记数）、impressions（曝光）、views（阅读）和 engagements（互动）。要看几个词就调几次。

cURLPythonTypeScript命令行

curl -G "https://api.dataxapi.com/v1/xiaohongshu/pgy/keywords/history" \
  --data-urlencode "keyword=面膜" \
  -H "Authorization: Bearer $DATAXAPI_API_KEY"

# pip install dataxapi
from dataxapi import DataXAPI

dx = DataXAPI()  # reads DATAXAPI_API_KEY
result = dx.xiaohongshu.pgy.keywords.history(keyword="面膜")
print(result["data"]["item"])

// npm i @dataxapi/sdk
import { DataXAPI } from "@dataxapi/sdk";

const dx = new DataXAPI(); // reads DATAXAPI_API_KEY
const result = await dx.xiaohongshu.pgy.keywords.history({ keyword: "面膜" });
console.log(result.data.item);

dataxapi call xiaohongshu.pgy.keywords.history 'keyword=面膜'

录制的返回

{
  "code": "ok",
  "request_id": "5303d79c-7963-4548-a038-ec91bd3cae60",
  "data": {
    "item": {
      "keyword": "露营",
      "points": [
        {
          "date": "2026-07-13T00:00:00Z",
          "search_index": 8876,
          "notes": 33361,
          "impressions": 25229649,
          "views": 4523846,
          "engagements": 188216
        },
        {
          "date": "2026-07-14T00:00:00Z",
          "search_index": 8762,
          "notes": 33750,
          "impressions": 24457001,
          "views": 4743520,
          "engagements": 197829
        },
        {
          "date": "2026-07-15T00:00:00Z",
          "search_index": 9077,
          "notes": 33603,
          "impressions": 24578646,
          "views": 4554487,
          "engagements": 210434
        },
        {
          "date": "2026-07-16T00:00:00Z",
          "search_index": 9328,
          "notes": 34232,
          "impressions": 28302245,
          "views": 4819305,
          "engagements": 220431
        },
        {
          "date": "2026-07-17T00:00:00Z",
          "search_index": 11233,
          "notes": 34532,
          "impressions": 32434694,
          "views": 5831644,
          "engagements": 278646
        },
        {
          "date": "2026-07-18T00:00:00Z",
          "search_index": 12636,
          "notes": 34772,
          "impressions": 35466179,
          "views": 6122704,
          "engagements": 279193
        },
        {
          "date": "2026-07-19T00:00:00Z",
          "search_index": 11490,
          "notes": 35368,
          "impressions": 37495492,
          "views": 8187198,
          "engagements": 302141
        },
        // … 另有 85 条
      ]
    }
  },
  "warnings": [],
  "meta": {
    "capability": "xiaohongshu.pgy.keywords.history",
    "result_status": "complete",
    "fetched_at": "2026-10-12T21:42:12.000Z",
    "cached": false,
    "replayed": false,
    "unavailable": { "points.composite_index": "platform" },
    "billing": {
      "amount": "0.04",
      "currency": "USD",
      "balance_after": "9.96"
    }
  }
}

小红书蒲公英关键词逐日搜索指数 · $0.0400 / 一次 · 参数、字段和报错见接口页 →

示例花多少钱

取一个词的关联词，再取这个词和排名第一的关联词逐日的数，一共两个词

接口调用次数单价小计

小红书蒲公英关联词1$0.0400$0.0400

小红书蒲公英关键词逐日搜索指数2$0.0400$0.0800

合计3$0.12

价格是生成本页时的现行价格。失败的调用不收费。

在 AI 里做（MCP）

把 DataXAPI 接进你的 AI 客户端，只要接一次。之后直接说要什么，代理自己找到这些接口、看好价格，用你的余额调用。

这样说: 用小红书蒲公英查“防晒”的关联词，挑排名第一的那个，和“防晒”一起取每天的搜索指数、笔记数和互动，整理成一张表。

代理发给 call 工具的参数

{
  "capability": "xiaohongshu.pgy.keywords.related",
  "keyword": "面膜",
  "idempotency_key": "<a new UUID>"
}

登录后复制带你 Key 的接入提示词了解 MCP 服务 →

要知道的

搜索指数是蒲公英自己给出的指数，不是搜索次数。适合拿一个词和它自己的过去比，或者和小红书上的另一个词比。
关联词接口没有结果时也收费；逐日指数接口查不到这个词时返回空结果，不收费。
日期是中国时间（UTC+8）的自然日。

完整脚本

上面这件事写成一个能直接跑的脚本：Python，用 SDK，Key 从 DATAXAPI_API_KEY 读。它写出一个 CSV 文件，最后打印调了几次、取到几条、扣了多少。

Python

# pip install dataxapi
# export DATAXAPI_API_KEY=dx_...   (your key)
import csv
from decimal import Decimal
from dataxapi import DataXAPI

dx = DataXAPI()
calls, fetched, charged = 0, 0, Decimal("0")

def run(capability, params):
    """One call; counts it and what it was charged."""
    global calls, charged
    result = dx.call(capability, params)
    calls += 1
    charged += Decimal(str(result["meta"]["billing"]["amount"]))
    return result

KEYWORD = "防晒"
MORE = 1

# 1. The keyword's related keywords on PGY, each with its search index.
related = run("xiaohongshu.pgy.keywords.related", {"keyword": KEYWORD})["data"]["items"]
words = [KEYWORD] + [each["keyword"] for each in sorted(related, key=lambda each: each.get("rank", 0))[:MORE]]

# 2. Each word's daily search index, notes, impressions, views and engagements.
rows = []
for word in words:
    item = run("xiaohongshu.pgy.keywords.history", {"keyword": word})["data"]["item"]
    if item:
        for point in item["points"]:
            rows.append([item["keyword"], point["date"], point.get("search_index"), point.get("notes"), point.get("impressions"), point.get("views"), point.get("engagements")])

fetched = len(rows)
with open("pgy-keywords.csv", "w", newline="", encoding="utf-8") as file:
    csv.writer(file).writerows([["keyword", "date", "search_index", "notes", "impressions", "views", "engagements"], *rows])

print(f"calls: {calls}, items: {fetched}, charged: ${charged}")

2026-10-29 真实跑过一次：调用 3 次，写出 182 行，扣费 $0.12。失败的调用不收费。

用到的接口

小红书蒲公英关联词小红书蒲公英关键词逐日搜索指数