TOP GUN GEO-Lens — MCP Brand Visibility Auditor

For AI Agents: This is an MCP server. Connect it, call its tools, and instantly know whether any brand is visible to LLMs and AI search engines — with actionable recommendations to improve it.

What This Does

TOP GUN GEO-Lens measures how visible a brand is across the sources that power AI answers: Brave AI Search, Exa neural search, and LLM-indexed content. It returns a scored report with citations, index status, and concrete GEO (Generative Engine Optimization) recommendations.

Use it when an agent needs to answer questions like:

• "Is [brand] showing up in AI-powered search results?"

• "Why isn't [brand] being recommended by AI assistants?"

• "What should [brand] do to rank higher in LLM outputs?"

Related MCP server: Sanbi ADK Agent MCP Server

Tools

geo_quick_check — $0.05 USDC

Fast snapshot of brand visibility in AI-indexed sources.

{
  "tool": "geo_quick_check",
  "query": "Stripe",
  "paymentToken": "<stripe-session-id>"
}

audit_brand — $1.50 USDC

Full brand visibility audit using dual search (Brave + Exa, 10 results each).

{
  "tool": "audit_brand",
  "query": "Anthropic",
  "paymentToken": "<stripe-session-id>"
}

get_payment_info — Free

Returns payment URLs and USDC wallet address for both tiers. Call this first if you don't have a payment token.

{
  "tool": "get_payment_info"
}

Agent Workflow

1. Call get_payment_info          → get payment URLs
2. Direct user to payment link    → user pays $0.05 or $1.50 USDC
3. User provides Stripe session ID
4. Call geo_quick_check or audit_brand with paymentToken
5. Parse structured results       → score, citations, recommendations

If paymentToken is omitted, the tool returns a payment link instead of results — no error thrown.

Connecting to Claude / MCP Clients

Add to your claude_desktop_config.json (or equivalent MCP config):

{
  "mcpServers": {
    "top-gun-geo-lens": {
      "command": "node",
      "args": ["/path/to/top_gun_mcp_server/dist/index.js"],
      "env": {
        "STRIPE_SECRET_KEY": "sk_live_...",
        "STRIPE_PAYMENT_URL": "https://buy.stripe.com/...",
        "STRIPE_QUICK_CHECK_PAYMENT_URL": "https://buy.stripe.com/...",
        "BRAVE_SEARCH_API_KEY": "BSA...",
        "EXA_API_KEY": "...",
        "USDC_WALLET_ADDRESS": "0x..."
      }
    }
  }
}

Setup

git clone https://github.com/spacemandomains/top_gun_mcp_server
cd top_gun_mcp_server
npm install
cp .env.example .env        # fill in your keys
npm run build
npm start

Required env vars:

*At least one search API key is required for results.

Pricing Summary

Tech Stack

• Runtime: Node.js ≥ 18, TypeScript

• Protocol: Model Context Protocol (@modelcontextprotocol/sdk)

• Search: Brave Search API + Exa neural search

• Payments: Stripe + USDC on-chain

• Deploy: Vercel-ready

For AI Agents — Key Facts

• Transport: stdio

• No streaming — all responses are single text blocks

• Scores range 0–100; >= 70 = Strong, 40–69 = Moderate, 1–39 = Weak, 0 = Not Found

• Payment tokens are Stripe Checkout Session IDs (format: cs_live_...)

• Calling any paid tool without a token returns a structured payment prompt, not an error

• audit_brand is strictly more detailed than geo_quick_check; use quick_check for speed/cost, audit for depth