mcpField
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ai-visibility

ai-visibility

Local
github.com/sharozdawaBusiness & Marketing11Updated 31w ago

About ai-visibility

ai-visibility is an MCP server for tracking how brands appear across ChatGPT, Perplexity, Claude, and Gemini. It is aimed at teams monitoring AI-platform visibility, with scores, sentiment and competitor analysis, plus recommendations.

Key features

  1. 01Track brand mentions across four platforms
  2. 02Visibility scores and tiers
  3. 03Sentiment and competitor analysis
  4. 04Compare multiple brands side by side
  5. 05Prioritized improvement recommendations
  6. 06Visual tracking dashboard

Use cases

  1. 01Check brand exposure in AI responses
  2. 02Compare a brand's presence with competitors
  3. 03Review mention sentiment and position by platform

MCP support

The server provides tools for brand and query checks, visibility scores, comparisons, recommendations, and platform listings to MCP clients such as Claude Desktop and Cursor.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"sharozdawa-ai-visibility": {
"command": "npx",
"args": [
"-y",
"ai-visibility-mcp"
]
}
}
}
Run commandnpx -y ai-visibility-mcp

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npmai-visibility-mcp1.0.0

Tools

6

Saved tool list · updated 2w ago

ParameterTypeRequiredDescription
brandstringYesThe brand name to check visibility for
keywordsarrayNoIndustry keywords related to the brand (e.g., ['SEO', 'analytics']). Used to generate relevant queries.
platformsarrayNoWhich AI platforms to check. Defaults to all four platforms.

Details

From the project README

README image

npm version GitHub stars License PRs Welcome AI Visibility MCP server

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:

{
  "mcpServers": {
    "ai-visibility": {
      "command": "npx",
      "args": ["-y", "ai-visibility-mcp"]
    }
  }
}
Cursor

Add to your Cursor MCP settings (.cursor/mcp.json):

{
  "mcpServers": {
    "ai-visibility": {
      "command": "npx",
      "args": ["-y", "ai-visibility-mcp"]
    }
  }
}
npx (standalone)
npx ai-visibility-mcp

MCP Tools

ToolDescription
check_brand_visibilityCheck a brand's visibility across AI platforms with detailed per-platform results, mention rates, positions, sentiment, and competitor analysis
check_single_queryCheck brand mention for a specific query on a specific platform — get mention status, position, context snippet, and sentiment
get_visibility_scoreCalculate overall AI visibility score (0-100) with tier rating, per-platform breakdowns, and improvement recommendations
compare_brandsCompare visibility of 2-10 brands side by side with ranked results and per-platform scores
get_recommendationsGet prioritized, actionable recommendations to improve AI visibility based on current score
list_platformsList 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:

ComponentWeightWhat It Measures
Mention Rate40%How often the brand appears in AI responses
Position Quality30%Where the brand is mentioned (1st = best, 5th = worst)
Sentiment30%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:

git clone https://github.com/sharozdawa/ai-visibility.git
cd ai-visibility/mcp-server
npm install
npm run build

Run the MCP server directly:

node dist/index.js

Or point your MCP client to the local build:

{
  "mcpServers": {
    "ai-visibility": {
      "command": "node",
      "args": ["/path/to/ai-visibility/mcp-server/dist/index.js"]
    }
  }
}
Run the Web Dashboard

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 dev

Platforms Tracked

PlatformCompanyHow It Sources Information
ChatGPTOpenAITrained on web data; optional web browsing for real-time info
PerplexityPerplexity AIReal-time web search with source citations
ClaudeAnthropicTrained on web data; focuses on accurate, well-reasoned responses
GeminiGoogleLeverages Google Search index and Knowledge Graph

Why AI Visibility vs Paid Alternatives

Featureai-visibilityOtterlyAthenaHQ
Platforms tracked432
Visibility scoreYesYesYes
Competitor analysisYesYesLimited
Sentiment analysisYesNoNo
Self-hostableYesNoNo
Open sourceYesNoNo
PriceFree$100-300/mo$200-500/mo

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ToolDescription
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indexnow-mcpInstant URL indexing via IndexNow
schema-genSchema.org JSON-LD markup generator

License

MIT


Built by Sharoz Dawa
GitHub

README image

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