The AI Visibility MCP server tracks and analyzes brand visibility across ChatGPT, Perplexity, Claude, and Gemini, providing actionable insights into how AI platforms mention and describe your brand.
Check Brand Visibility — Analyze a brand's presence across all four AI platforms, including mention rates, positions, sentiment analysis, and competitor landscape using relevant industry keywords.
Check Single Query — Test a specific query on a specific platform to see if/how your brand is mentioned, with position, context snippet, sentiment, and competing brands.
Get Visibility Score — Generate an overall 0–100 visibility score with per-platform breakdowns and tier ratings (Very Low → Excellent).
Compare Brands — Side-by-side comparison of 2–10 brands, showing per-platform scores, rankings, and relative strengths.
Get Recommendations — Prioritized, actionable steps to improve AI visibility based on current score and industry best practices.
List Platforms — View details on all supported AI platforms, including how each sources and presents brand information.
Monitors brand visibility and performance within Google's Gemini AI, analyzing how the platform presents brand information sourced from the Google Knowledge Graph and Search index.
Tracks brand mentions, sentiment, and ranking position within OpenAI's ChatGPT platform to assess AI-driven brand awareness and visibility.
Monitors brand visibility and mention frequency within Perplexity AI, analyzing how the platform cites and describes brands in real-time search-augmented responses.
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
Related MCP server: indexnow-mcp
Add to your claude_desktop_config.json:
{
"mcpServers": {
"ai-visibility": {
"command": "npx",
"args": ["-y", "ai-visibility-mcp"]
}
}
}Add to your Cursor MCP settings (.cursor/mcp.json):
{
"mcpServers": {
"ai-visibility": {
"command": "npx",
"args": ["-y", "ai-visibility-mcp"]
}
}
}npx ai-visibility-mcpTool | Description |
| Check a brand's visibility across AI platforms with detailed per-platform results, mention rates, positions, sentiment, and competitor analysis |
| Check brand mention for a specific query on a specific platform — get mention status, position, context snippet, and sentiment |
| Calculate overall AI visibility score (0-100) with tier rating, per-platform breakdowns, and improvement recommendations |
| Compare visibility of 2-10 brands side by side with ranked results and per-platform scores |
| Get prioritized, actionable recommendations to improve AI visibility based on current score |
| List all supported AI platforms with details on how each sources and presents brand information |
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
Clone the repo and build the MCP server:
git clone https://github.com/sharozdawa/ai-visibility.git
cd ai-visibility/mcp-server
npm install
npm run buildRun the MCP server directly:
node dist/index.jsOr point your MCP client to the local build:
{
"mcpServers": {
"ai-visibility": {
"command": "node",
"args": ["/path/to/ai-visibility/mcp-server/dist/index.js"]
}
}
}The project includes a Next.js dashboard for visual tracking:
cd ai-visibility
cp .env.example .env
# Set your DATABASE_URL in .env
npm install
npx prisma db push
npm run devPlatform | 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 |
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 |
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MIT
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Brand visibility auditing across LLMs, AI search, and answer engines with GEO reports and scores.
AI brand visibility analytics: visibility scores, optimizations, video, Reddit, and search rankings.
AI visibility analytics for brand mentions, citations, sentiment, and GEO reports
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