claude mcp add ai-visibility -- npx -y ai-visibility
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
10 ★ · sharozdawa/ai-visibility · read from the GitHub search API · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 10 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository sharozdawa/ai-visibility;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
Third-party quality signals
Know exactly how AI platforms talk about your brand.
Track mentions, sentiment, position, and competitors across the AI platforms that shape buying decisions. --- Features - **Multi-Platform Tracking** — Monitor visibility across ChatGPT, Perplexity, Claude, and Gemini simultaneously - **Visibility Scoring** — Get a 0-100 score with tier ratings (Excellent / Good / Moderate / Low / Very Low) - **Sentiment Analysis** — Understand whether AI platforms describe your brand positively, neutrally, or negatively - **Competitor Intelligence** — See which competitors appear alongside your brand in AI responses - **Brand Comparison** — Compare up to 10 brands side by side with per-platform breakdowns - **Actionable Recommendations** — Get prioritized steps to improve your AI visibility - **MCP Server** — Works with Claude Desktop, Cursor, and any MCP-compatible client - **Consistent Results** — Seeded randomness ensures reproducible results for the same brand MCP Server Installation Claude Desktop Add to your claude_desktop_config.json: Cursor Add to your Cursor MCP settings (.cursor/mcp.json): npx (standalone) MCP Tools | Tool | Description | |------|-------------| | check_brand_visibility | Check a brand's visibility across AI platforms with detailed per-platform results, mention rates, positions, sentiment, and competitor analysis | | check_single_query | Check brand mention for a specific query on a specific platform — get mention status, position, context snippet, and sentiment | | get_visibility_score | Calculate overall AI visibility score (0-100) with tier rating, per-platform breakdowns, and improvement recommendations | | compare_brands | Compare visibility of 2-10 brands side by side with ranked results and per-platform scores | | get_recommendations | Get prioritized, actionable recommendations to improve AI visibility based on current score | | list_platforms | List all supported AI platforms with details on how each sources and presents brand information | How Scoring Works The visibility score (0-100) is calculated from three components: | Component | Weight | What It Measures | |-----------|--------|-----------------| | Mention Rate | 40% | How often the brand appears in AI responses | | Position Quality | 30% | Where the brand is mentioned (1st = best, 5th = worst) | | Sentiment | 30% | Whether mentions are positive, neutral, or negative | **Score Tiers:** - **80-100** Excellent — Strong presence across platforms - **60-79** Good — Visible but room to improve - **40-59** Moderate — Appears in some responses - **20-39** Low — Limited visibility - **0-19** Very Low — Rarely mentioned Self-Hosting Clone the repo and build the MCP server: Run the MCP server directly: Or point your MCP client to the local build: Run the Web Dashboard The project includes a Next.js dashboard for visual tracking: Platforms Tracked | Platform | Company | How It Sources Information |