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 |
|---|---|---|
| ChatGPT | OpenAI | Trained on web data; optional web browsing for real-time info |
| Perplexity | Perplexity AI | Real-time web search with source citations |
| Claude | Anthropic | Trained on web data; focuses on accurate, well-reasoned responses |
| Gemini | Leverages Google Search index and Knowledge Graph |
Why AI Visibility vs Paid Alternatives
| Feature | ai-visibility | Otterly | AthenaHQ |
|---|---|---|---|
| Platforms tracked | 4 | 3 | 2 |
| Visibility score | Yes | Yes | Yes |
| Competitor analysis | Yes | Yes | Limited |
| Sentiment analysis | Yes | No | No |
| Self-hostable | Yes | No | No |
| Open source | Yes | No | No |
| Price | Free | $100-300/mo | $200-500/mo |
More Open Source SEO Tools
| Tool | Description |
|---|---|
| awesome-seo-mcp-servers | Curated list of SEO MCP servers and agent skills |
| robotstxt-ai | Visual robots.txt manager for AI crawlers |
| indexnow-mcp | Instant URL indexing via IndexNow |
| schema-gen | Schema.org JSON-LD markup generator |
License
MIT
Built by Sharoz Dawa
