CommunityMentions
Which subreddits AI answers cite, matched to your product, with each one's most-cited threads.
我该使用它吗
质量与安全性
A
基于对工具定义和协议合规性的自动分析。
上下文开销
~1,314token 数（工具定义）
~6.1 KB典型响应大小
对注意力有中等影响（占 128k 上下文窗口的 1.03%）
这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高，可用于其他任务的注意力就越少。
安装
一键安装
将以下内容添加到你的 `claude_desktop_config.json` 文件中：
{
"mcpServers": {
"communitymentions": {
"url": "https://communitymentions.com/api/mcp"
}
}
}远程端点
https://communitymentions.com/api/mcpstreamable-http它能做什么
工具清单
工具（2）
🟢 只读🟡 写入🔴 删除⚪ 未知
🟢find_subreddits(description)
Use this when someone asks which subreddits or Reddit communities fit a product, brand or niche, or where on Reddit AI answers look for recommendations in a category. Takes a short description such as "AI writing tool for marketers" and returns up to 10 matching subreddits, closest match first, with how often AI answers cited each, members and a link to each subreddit's data page. Only subreddits in CommunityMentions' data (cited 50+ times or with 50+ verified comments placed) are included; health, legal-help and adult communities are left out.
输入模式
{
"type": "object",
"properties": {
"description": {
"type": "string",
"minLength": 2,
"maxLength": 120,
"description": "What the product or niche is, in a few words"
}
},
"required": [
"description"
],
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}输出模式
{
"type": "object",
"properties": {
"matches": {
"type": "array",
"items": {
"type": "object",
"properties": {
"subreddit": {
"type": "string"
},
"category": {
"type": "string"
},
"members": {
"type": [
"number",
"null"
]
},
"ai_citations": {
"type": [
"number",
"null"
]
},
"ai_answers_citing": {
"type": [
"number",
"null"
]
},
"threads_cited": {
"type": [
"number",
"null"
]
},
"verified_comments_placed": {
"type": [
"number",
"null"
]
},
"page_url": {
"type": "string"
}
},
"required": [
"subreddit",
"category",
"members",
"ai_citations",
"ai_answers_citing",
"threads_cited",
"verified_comments_placed",
"page_url"
],
"additionalProperties": false
}
},
"matched_on": {
"type": "array",
"items": {
"type": "string"
}
},
"no_close_match": {
"type": "boolean"
},
"median_ai_citations": {
"type": "number"
},
"data_as_of": {
"type": "string"
}
},
"required": [
"matches",
"matched_on",
"no_close_match",
"median_ai_citations",
"data_as_of"
],
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢get_subreddit(subreddit)
Use this when someone asks how often AI answers cite a specific subreddit, which of its threads get cited, or whether it matters for being recommended by ChatGPT, Perplexity or Gemini. Takes a subreddit name such as "SaaS" or "r/marketing" and returns its AI citations by engine, the kinds of questions those answers were about, its most-cited threads and its member count.
输入模式
{
"type": "object",
"properties": {
"subreddit": {
"type": "string",
"minLength": 2,
"maxLength": 60,
"description": "A subreddit name, with or without r/"
}
},
"required": [
"subreddit"
],
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}输出模式
{
"type": "object",
"properties": {
"found": {
"type": "boolean"
},
"subreddit": {
"anyOf": [
{
"type": "object",
"properties": {
"subreddit": {
"type": "string"
},
"category": {
"type": "string"
},
"members": {
"type": [
"number",
"null"
]
},
"ai_citations": {
"type": [
"number",
"null"
]
},
"ai_answers_citing": {
"type": [
"number",
"null"
]
},
"threads_cited": {
"type": [
"number",
"null"
]
},
"verified_comments_placed": {
"type": [
"number",
"null"
]
},
"page_url": {
"type": "string"
},
"rank_by_ai_citations": {
"type": [
"number",
"null"
]
},
"cited_from": {
"type": [
"string",
"null"
]
},
"cited_to": {
"type": [
"string",
"null"
]
},
"citations_by_engine": {
"anyOf": [
{
"type": "object",
"properties": {
"openai_models": {
"type": [
"number",
"null"
]
},
"perplexity": {
"type": [
"number",
"null"
]
},
"gemini": {
"type": [
"number",
"null"
]
}
},
"required": [
"openai_models",
"perplexity",
"gemini"
],
"additionalProperties": false
},
{
"type": "null"
}
]
},
"citing_answers_by_question_type": {
"anyOf": [
{
"type": "object",
"properties": {
"comparing_products": {
"type": [
"number",
"null"
]
},
"looking_to_buy": {
"type": [
"number",
"null"
]
},
"describing_a_problem": {
"type": [
"number",
"null"
]
}
},
"required": [
"comparing_products",
"looking_to_buy",
"describing_a_problem"
],
"additionalProperties": false
},
{
"type": "null"
}
]
},
"most_cited_threads": {
"type": "array",
"items": {
"type": "object",
"properties": {
"title": {
"type": "string"
},
"url": {
"type": "string"
},
"ai_citations": {
"type": "number"
}
},
"required": [
"title",
"url",
"ai_citations"
],
"additionalProperties": false
}
}
},
"required": [
"subreddit",
"category",
"members",
"ai_citations",
"ai_answers_citing",
"threads_cited",
"verified_comments_placed",
"page_url",
"rank_by_ai_citations",
"cited_from",
"cited_to",
"citations_by_engine",
"citing_answers_by_question_type",
"most_cited_threads"
],
"additionalProperties": false
},
{
"type": "null"
}
]
},
"suggestions": {
"type": "array",
"items": {
"type": "object",
"properties": {
"subreddit": {
"$ref": "#/properties/subreddit/anyOf/0/properties/subreddit"
},
"category": {
"$ref": "#/properties/subreddit/anyOf/0/properties/category"
},
"members": {
"$ref": "#/properties/subreddit/anyOf/0/properties/members"
},
"ai_citations": {
"$ref": "#/properties/subreddit/anyOf/0/properties/ai_citations"
},
"ai_answers_citing": {
"$ref": "#/properties/subreddit/anyOf/0/properties/ai_answers_citing"
},
"threads_cited": {
"$ref": "#/properties/subreddit/anyOf/0/properties/threads_cited"
},
"verified_comments_placed": {
"$ref": "#/properties/subreddit/anyOf/0/properties/verified_comments_placed"
},
"page_url": {
"$ref": "#/properties/subreddit/anyOf/0/properties/page_url"
}
},
"required": [
"subreddit",
"category",
"members",
"ai_citations",
"ai_answers_citing",
"threads_cited",
"verified_comments_placed",
"page_url"
],
"additionalProperties": false
}
}
},
"required": [
"found",
"subreddit",
"suggestions"
],
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}社区
证据
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