参数
| 参数 | 必填 | 取值 |
|---|---|---|
| platform | 是 | tiktok / youtube / twitter / douyin / xiaohongshu / instagram |
| post_id | 是 | 内容 id(也可直接传视频链接里的数字 id) |
| sample | 否 | 采样评论条数,默认 50,越大越慢 |
返回什么
字段与平台无关:帖子类 items[](url、文案、作者、时间、互动数据、封面),达人类 items[](handle、昵称、简介、粉丝数、认证),洞察类直接给 sentiment / questions / top_phrases / top_liked / summary。
在 MCP 客户端里怎么用
不需要记参数——把端点加进客户端后,直接用自然语言描述需求,模型会自己挑工具和参数。写代码时再用上面的 REST 形式。
复制即可运行
cURL
curl -s https://lucydomi.com/mcp/v1/get_comment_insights \
-H "Authorization: Bearer $BUSYBEE_API_KEY" \
-H "Content-Type: application/json" \
-X POST \
-d '{"platform": "tiktok", "post_id": "7690199760430566669", "sample": 20}'Python(标准库)
import os, json, urllib.request
KEY = os.environ["BUSYBEE_API_KEY"]
req = urllib.request.Request(
"https://lucydomi.com/mcp/v1/get_comment_insights",
data=json.dumps({"platform": "tiktok", "post_id": "7690199760430566669", "sample": 20}).encode(),
headers={"Authorization": f"Bearer {KEY}", "Content-Type": "application/json"},
method="POST",
)
data = json.load(urllib.request.urlopen(req, timeout=60))
for it in data["items"]:
print(it.get("url"), it.get("text", "")[:60])真实返回样例
下面这段是线上真实返回(已截断到 1 条,去掉了计费字段)。
{
"total": 20,
"sentiment": {
"positive": 2,
"negative": 0,
"neutral": 18,
"positive_hits": 3,
"negative_hits": 0
},
"questions": {
"count": 9,
"ratio": 0.45
},
"engagement": {
"max_likes": 1103,
"avg_likes": 78.4
},
"top_phrases": [
{
"phrase": "spanish",
"count": 5
},
{
"phrase": "coffee",
"count": 3
},
{
"phrase": "watery",
"count": 3
},
{
"phrase": "ice",
"count": 3
},
{
"phrase": "honey",
"count": 2
},
{
"phrase": "latte",
"count": 2
},
{
"phrase": "spain",
"count": 2
},
{
"phrase": "sooo",
"count": 2
},
{
"phrase": "good",
"count": 2
}
],
"top_liked": [
{
"text": "Make it three",
"likes": 1103,
"author": "Samantha"
},
{
"text": "how do u guys prevent the coffee from being watery? when i put a lot of ice it gets watery fast, or am i just drinking it too slowly 🥲",
"likes": 145,
"author": "lex"
},
{
"text": "The honey? the salt? the cinnamon??? Disastrous.",
"likes": 135,
"author": "bubibat"
},
{
"text": "Where’s the name “Spanish latte” coming from? Because this is not a normal coffee in Spain. It would be a café bombón",
"likes": 52,
"author": "angelagvarela"
},
{
"text": "What makes it Spanish?",
"likes": 31,
"author": "Arturo Hlebov"
}
],
"summary": "共分析 20 条评论;其中 9 条(45%)是提问,说明购买意图明确;情绪正面为主(正面 2 条 / 负面 0 条);高频词:spanish、coffee、watery、ice、honey;单条最高点赞 1103",
"post": {
"platform": "tiktok",
"id": "7690199760430566669",
"text": null,
"stats": {}
},
"ok": true,
"platform": "tiktok",
"tool": "get_comment_insights",
"sampled": 20
}常见问题
这个工具和直接搜关键词有什么区别?
搜关键词给你原始条目,评论洞察给你结论(情绪比例、提问占比、高频词、高赞评论),省一轮后处理。
采样条数越大越准吗?
更稳但更慢。判断选题 20-50 条足够;要严谨统计再往上调。
失败会扣次数吗?
不会。上游失败自动退款,只有拿到数据才算一次。