mentiondrop
AI-triaged brand, competitor and demand mentions from Reddit, Google News and search.
Should I use this
Quality & Safety
Findings (1)
- LOWTool 'get_competitor_signals' description lacks action verbin get_competitor_signals
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"mentiondrop": {
"url": "https://www.mentiondrop.com/api/mcp"
}
}
}Remote endpoints
https://www.mentiondrop.com/api/mcpstreamable-httpWhat it can do
Tool inventory
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.
Input 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.
Input 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.
Input 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".
Input 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.
Input 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.
Input 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.
Input 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.
Input 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.
Input 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.
Input 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.
Input Schema
{
"type": "object",
"properties": {
"mention_id": {
"type": "string"
},
"draft_intent": {
"type": "string",
"enum": [
"reply",
"outreach_email"
]
}
},
"required": [
"mention_id"
],
"additionalProperties": false
}Community
Evidence