{"name":"ReviewResponder","version":"1.0.0","description":"Draft replies to your reviews","url":"https://review-responder.magicteams.ai","mcp_endpoint":"https://review-responder.magicteams.ai/mcp","protocol":"mcp-streamable-http","authentication":"none","pricing":"free","tools":[{"name":"draft_review_reply","title":"Draft review reply","description":"Draft one owner reply to a Google or Yelp review you paste in, from the review text, star rating, business name and tone (warm, professional or concise), following platform best practice: thank, address the specifics named, apologize for negatives without arguing, move 1-3 star issues offline, under 120 words, no incentives. Returns the draft plus a checklist. Use for a single review. Do NOT use for several reviews at once; use batch_draft_replies."},{"name":"batch_draft_replies","title":"Batch draft replies","description":"Draft replies for 1-25 pasted reviews and order them by urgency: unreplied 1-2 star reviews first, then 3 star, then 4-5 star, oldest first within each band. Returns a numbered reply order with a draft, urgency and reason for each, plus counts. Use when catching up on a backlog. Do NOT use to find recurring themes; use analyze_review_themes."},{"name":"analyze_review_themes","title":"Analyze review themes","description":"Summarize 1-50 pasted reviews: rating distribution and average, recurring positive and negative themes from a fixed keyword lexicon (service, wait time, price, cleanliness, staff, quality, booking, parking, communication, atmosphere, accuracy) with mention counts and a sample quote each, top praise and complaint quotes, and a suggested fix per negative theme. Use to see what customers keep saying. Do NOT use to write replies; use batch_draft_replies."},{"name":"estimate_response_impact","title":"Estimate response impact","description":"Estimate what answering reviews consistently is worth for a local business: replies needed per month at a target response rate (default 90%), hours per month with drafts versus writing by hand, a rating-lift range over 12 months and revenue at stake from average ticket and monthly customers. Built-in typical estimates per business type (restaurant, salon, dental, auto_repair, hotel, gym, retail, home_services, clinic, cafe) fill any number you do not give; ranges are labelled planning assumptions. Use to decide whether a reply routine is worth the time. Do NOT use to set response-time targets; use build_response_sla."},{"name":"build_response_sla","title":"Build response policy","description":"Build a review-response policy for your team: target response time per star band (default 1-2 stars within 24h, 3 stars 48h, 4-5 stars one week), who drafts and who approves, a weekly check schedule sized to your review volume, escalation triggers and a template bank per star band with placeholders. Use when setting up a routine. Do NOT use to size the benefit; use estimate_response_impact."},{"name":"flag_policy_risks","title":"Flag policy risks","description":"Scan a drafted reply (or a review) for wording that breaks Google or Yelp guidelines or creates legal exposure: offering incentives, asking for a rating change, soliciting fake reviews, revealing private or health details, legal threats, admitting liability, discriminatory language, arguing, profanity. Returns flags with severity, the matched text, why it matters and a fix, plus a risk level. Use before posting any reply. Do NOT use to write the reply; use draft_review_reply."}],"directories":{"chatgpt":"https://platform.openai.com/plugins","claude":"https://claude.ai/directory/manage","muse":"https://muse.ai/platform","registry":"https://registry.modelcontextprotocol.io/servers/io.github.everyai-com/review-responder","smithery":"https://smithery.ai/servers/tradephani/review-responder"},"llms_txt":"https://review-responder.magicteams.ai/llms.txt","ucp_profile":"https://review-responder.magicteams.ai/.well-known/ucp","support":"https://review-responder.magicteams.ai/support","operator":"MagicTeams <support@magicteams.ai>"}