mentiondrop
AI-triaged brand, competitor and demand mentions from Reddit, Google News and search.
Sollte ich dies verwenden
Qualität und Sicherheit
Befunde (1)
- LOWTool 'get_competitor_signals' description lacks action verbin get_competitor_signals
Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.
Kontextkosten
Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.
Installieren
Installation mit einem Klick
Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:
{
"mcpServers": {
"mentiondrop": {
"url": "https://www.mentiondrop.com/api/mcp"
}
}
}Remote-Endpunkte
https://www.mentiondrop.com/api/mcpstreamable-httpWas es kann
Tool-Inventar
Tools (11)
🟢list_keywords
List every keyword this MentionDrop account monitors, with its id, role (own_brand, competitor, or industry), and active state. Call this first to discover the keyword ids and role names the other tools accept.
Eingabe-Schema
{
"type": "object",
"properties": {},
"additionalProperties": false
}🟡create_keyword(keyword, role, context)
Start monitoring a new keyword for this account. Takes an optional role (own_brand, competitor, or industry) and a short context string that sharpens relevance scoring. Enforces the account plan keyword limit and rejects keywords too generic to produce signal.
Eingabe-Schema
{
"type": "object",
"properties": {
"keyword": {
"type": "string",
"minLength": 2,
"maxLength": 100
},
"role": {
"type": "string",
"enum": [
"own_brand",
"competitor",
"industry"
]
},
"context": {
"type": "string",
"maxLength": 300
}
},
"required": [
"keyword"
],
"additionalProperties": false
}🟡update_keyword(id, is_active, context, role, excluded_content_types, ...)
Update one existing monitored keyword by id: change its role, context, active state, minimum relevance threshold, excluded content types, or exclusion terms. Use list_keywords to find the id. Pausing a keyword sets is_active to false rather than deleting it.
Eingabe-Schema
{
"type": "object",
"properties": {
"id": {
"type": "string"
},
"is_active": {
"type": "boolean"
},
"context": {
"type": [
"string",
"null"
]
},
"role": {
"type": "string",
"enum": [
"own_brand",
"competitor",
"industry"
]
},
"excluded_content_types": {
"type": "array",
"items": {
"type": "string"
}
},
"exclusion_terms": {
"type": "array",
"items": {
"type": "string"
}
},
"min_relevance": {
"type": "number",
"minimum": 0,
"maximum": 100
}
},
"required": [
"id"
],
"additionalProperties": false
}🟢get_recent_mentions(role, keyword, source, sentiment, from, ...)
Return the most recent mentions matched for this account, newest first, each with its AI summary, sentiment, relevance score, and suggested action. Filter by keyword role, specific keyword, source, sentiment, and date range. Use this to answer "what came in lately".
Eingabe-Schema
{
"type": "object",
"properties": {
"role": {
"type": "string",
"enum": [
"own_brand",
"competitor",
"industry"
]
},
"keyword": {
"type": "string"
},
"source": {
"type": "string",
"enum": [
"firehose",
"reddit",
"brave",
"google_news",
"serper",
"hackernews",
"adzuna"
]
},
"sentiment": {
"type": "string",
"enum": [
"positive",
"neutral",
"negative"
]
},
"from": {
"type": "string"
},
"to": {
"type": "string"
},
"limit": {
"type": "number",
"minimum": 1,
"maximum": 50
}
},
"additionalProperties": false
}🟢search_mentions(query, role, keyword, source, sentiment, ...)
Find mentions whose title, summary, URL, suggested action, or matched keyword contain every word in the query. Use this to look for a specific topic, product, or phrase rather than a plain time window.
Eingabe-Schema
{
"type": "object",
"properties": {
"query": {
"type": "string"
},
"role": {
"type": "string",
"enum": [
"own_brand",
"competitor",
"industry"
]
},
"keyword": {
"type": "string"
},
"source": {
"type": "string",
"enum": [
"firehose",
"reddit",
"brave",
"google_news",
"serper",
"hackernews",
"adzuna"
]
},
"sentiment": {
"type": "string",
"enum": [
"positive",
"neutral",
"negative"
]
},
"from": {
"type": "string"
},
"to": {
"type": "string"
},
"limit": {
"type": "number",
"minimum": 1,
"maximum": 50
}
},
"required": [
"query"
],
"additionalProperties": false
}🟢get_competitor_signals(competitor, from, to, limit)
Return recent mentions matched by competitor-role keywords, optionally narrowed to a single competitor name. Use this to see what people are publicly saying about rival products.
Eingabe-Schema
{
"type": "object",
"properties": {
"competitor": {
"type": "string"
},
"from": {
"type": "string"
},
"to": {
"type": "string"
},
"limit": {
"type": "number",
"minimum": 1,
"maximum": 50
}
},
"additionalProperties": false
}🟢get_pain_signals(keyword, from, to, limit)
Return recent industry-role mentions that read as demand or pain signals, meaning they carry a suggested action or score at least 80 for relevance. Use this to find people publicly describing a problem the product solves.
Eingabe-Schema
{
"type": "object",
"properties": {
"keyword": {
"type": "string"
},
"from": {
"type": "string"
},
"to": {
"type": "string"
},
"limit": {
"type": "number",
"minimum": 1,
"maximum": 50
}
},
"additionalProperties": false
}🟢get_digest(from, to, limit)
Return one grouped catch-up brief of recent mentions, split into owned brand mentions, competitor signals, demand signals, and conversations worth replying to. Use this when a single summary is wanted instead of separate queries.
Eingabe-Schema
{
"type": "object",
"properties": {
"from": {
"type": "string"
},
"to": {
"type": "string"
},
"limit": {
"type": "number",
"minimum": 1,
"maximum": 50
}
},
"additionalProperties": false
}🟢get_mention(id)
Fetch one mention by id with its full record: title, AI summary, sentiment, relevance score, suggested action, source, and matched keyword. Only returns mentions owned by this account.
Eingabe-Schema
{
"type": "object",
"properties": {
"id": {
"type": "string"
}
},
"required": [
"id"
],
"additionalProperties": false
}⚪mark_mention_reviewed(id, verdict)
Record a review verdict on one mention as relevant or not_relevant. This feedback tunes how future mentions are scored for the account. Re-sending the same verdict is safe.
Eingabe-Schema
{
"type": "object",
"properties": {
"id": {
"type": "string"
},
"verdict": {
"type": "string",
"enum": [
"relevant",
"not_relevant"
]
}
},
"required": [
"id",
"verdict"
],
"additionalProperties": false
}⚪generate_reply_draft(mention_id, draft_intent)
Generate a draft reply or outreach email for one processed mention. Returns draft text for a human to review and never posts, sends, or publishes anything.
Eingabe-Schema
{
"type": "object",
"properties": {
"mention_id": {
"type": "string"
},
"draft_intent": {
"type": "string",
"enum": [
"reply",
"outreach_email"
]
}
},
"required": [
"mention_id"
],
"additionalProperties": false
}Community
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