MentionDrop
8 billion pages scanned every day. Your brand found!
152 followers
8 billion pages scanned every day. Your brand found!
152 followers
Monitor the entire web: blogs, forums, docs, foreign-language sites, and more. Every mention gets an AI summary, sentiment score, and suggested action.
This is the 2nd launch from MentionDrop. View more
MentionDrop MCP
Launching today
MentionDrop MCP connects Claude, Cursor, Windsurf, and other MCP-aware agents to live brand monitoring. Your agent pulls brand mentions, competitor conversations, and public customer pain from bounded high-signal sources (Reddit, Google News, search, selected public web), triages them, and drafts replies for your review. 11 tools, account-scoped API keys, nothing auto-posted. Ask "what should I pay attention to today?" and get an answer you can act on.
Free Options
Launch Team
KeyStrokes
Hey Product Hunt! 👋
I'm Marcos, maker of MentionDrop.
MentionDrop watches the places where buyers actually talk: Reddit, Google News, search results, and selected public web pages. AI triages every mention: summary, sentiment, relevance, and whether to reply, share, monitor, or ignore.
Today's launch gives your AI agent that same view. Connect Claude, Cursor, or Windsurf with an API key and ask:
"What should I pay attention to today?"
"Find competitor complaints from the last 7 days"
"Draft a reply for the most urgent mention"
11 tools, read-first design. Your agent drafts, you decide what gets posted.
Honest boundaries: we do not monitor X, LinkedIn, or "the whole internet". Bounded sources, useful mentions.
Launch offer: 14-day free trial plus free MCP setup help. I will personally help you create your first monitors and connect your agent.
Tell me what your agent workflow needs. Ask me anything!
love that you name the limits out loud (no X, no 'whole internet') instead of overclaiming. does the agent learn which sources matter per brand over time?
KeyStrokes
The 'suggested action: reply / share / monitor / ignore' field is the interesting bit once this is behind MCP. When Claude or Cursor pulls a mention in, does that action come back as a plain label the agent re-reasons over, or is it structured enough to wire straight into an autonomous loop? The failure mode I keep hitting with signal-feed MCPs is the agent slurping 40 mentions into context and burning the window before it ever triages, so I'm curious whether you pre-rank or paginate server-side rather than handing back the raw firehose.
The nothing-auto-posted, drafts-for-review boundary is the right default for an MCP tool — an agent that has live web signal AND can publish is how brand incidents happen. With account-scoped API keys, is a key's rate/quota shared across all 11 tools or metered per tool, and can I scope one key to read-only mention pulls without exposing the reply-drafting tools? I'd want to hand a teammate's agent the monitoring half without the outreach half.
The sentiment score on mentions is useful but the suggested action is the harder part to get right, since the right action for a negative Reddit thread about your product depends heavily on context that's hard to capture automatically, like whether it's a power user venting or a prospect researching. How does MentionDrop avoid the suggested action defaulting to "respond and engage" for everything, which would just be noise?
The MCP angle here is smart, pulling this into the agent's workflow instead of another dashboard to check. Question on the foreign-language sites part of the pitch - sentiment scoring is already tricky in English with sarcasm and industry slang, how does accuracy hold up once you're scoring sentiment on a mention that's been through translation first? That seems like the place this could quietly go wrong without anyone noticing until a genuinely bad mention gets triaged as neutral.
Skipping X and LinkedIn is an honest call, but that's often where brand mentions actually happen for consumer products. How do teams work around that gap, run a separate tool alongside MentionDrop for those platforms?