MentionDrop MCP - Give your AI agent live market signals

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?

Could this be used to monitor product launches like Product Hunt and automatically surface high-priority conversations?

Congrats on the launch — market signals as an MCP server is a genuinely useful primitive.

One thing I noticed while poking around (compliance is my day job): the site fires GA/GTM before any consent for EU visitors — currently the most-fined ePrivacy gap, and it lands on small operators specifically. Easy fix: consent-gate the scripts or go cookieless.

Good luck — the agent-tooling wave needs more of this.

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?

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?

How does it decide which sources count as relevant mentions, and is there any way to scope it down so it doesn't drown me in noise from tangentially related sites?