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Ai Visibility Mcp

Ai Visibility Mcp

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github.com/krissandersBusiness & Marketing1Updated 23w ago

About Ai Visibility Mcp

Ai Visibility Mcp is an MCP server for site owners and marketing teams assessing how AI crawlers and search systems see their websites. It also generates robots.txt, JSON-LD, and llms.txt changes for an audit-and-review loop.

Key features

  1. 01Check access rules for 22 AI crawlers
  2. 02Score AI visibility with explained deductions
  3. 03Compare audits across multiple sites
  4. 04Check brand mentions across LLMs
  5. 05Generate robots.txt, JSON-LD, and llms.txt

Use cases

  1. 01Find AI crawler blocks in robots.txt or Cloudflare
  2. 02Spot missing structured data or llms.txt
  3. 03Compare a site’s AI visibility with competitors
  4. 04Check whether a brand appears in LLM answers

MCP support

Exposes website auditing, brand-mention checks, and corrective-file generation as tools to MCP clients.

Configuration

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

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

ai-visibility-mcp

MCP server that audits and fixes how AI sees your website. Robots, schema, LLM mentions, Cloudflare AI defaults — audit the problem, generate the fix, re-audit in one loop.

Python MCP License: MIT

Most websites are accidentally invisible to AI search. Cloudflare's bot-management defaults block GPTBot / ClaudeBot / PerplexityBot. SPAs render an empty <div id="root"> to crawlers that don't run JS. Marketing teams have no idea their brand isn't surfacing in ChatGPT, Claude, or Perplexity answers — until traffic dries up.

ai-visibility-mcp closes the audit-and-fix loop inside a single agent session:

  1. Audit — find what's blocking AI visibility
  2. Fix — generate the artifact that corrects it
  3. Paste — site owner applies the output
  4. Re-audit — verify the fix was picked up

Tools

Audit tools
ToolPurposeNeeds API keys?
check_ai_bot_access(domain)Per-bot robots.txt + Cloudflare AI-default flag for 22 AI user-agentsNo
audit_ai_visibility(domain)0-100 composite score with explainable deductions (robots, meta, JSON-LD, sitemap, llms.txt, SPA shell)No
check_llm_mention(brand, query, aliases?, models?)Cross-model brand surfacing (Perplexity sonar + OpenAI gpt-4o-mini + Gemini 2.0 Flash by default)Yes
compare_competitors(your_domain, competitor_domains[])Parallel ranked audit, max 10 in flightNo
Generator tools (v0.3)
ToolPurposeLLM call?
generate_robots_patch(domain, allow_bots?, deny_bots?)Corrected robots.txt that opens access to AI bots; preserves existing rules; detects CloudflareNo
generate_json_ld(url, page_type?)Schema.org JSON-LD block for any page; auto-detects type (Product/Article/Organization/FAQPage/SoftwareApplication/WebSite); validates required fieldsYes (gpt-4o-mini)
generate_llms_txt(domain, crawl_depth?, max_pages?)spec-compliant llms.txt; crawls homepage + sitemap; graceful fallback to link extractionYes (gpt-4o-mini)

Why this exists

  • Cloudflare flipped defaults in 2024-2025 to block AI scrapers. Most site owners never updated their config, so AI bots get challenged and bounce.
  • MCP marketplaces shipped in 2026 (MCP Hive, Smithery, mcp.so, Glama). Every AI agent needs tools that can audit the real web. This is one.
  • Brand visibility in LLM answers is the new SEO. Nobody has a clean stack for measuring it from a single MCP call.

Install

Requires Python 3.10+ and uv.

git clone https://github.com/bestaiinsider/ai-visibility-mcp
cd ai-visibility-mcp
uv sync
cp .env.example .env  # fill in PERPLEXITY_API_KEY / OPENROUTER_API_KEY

Run

# stdio transport — Claude Desktop / Claude Code
uv run ai-visibility-mcp

# HTTP transport — remote agents
uv run ai-visibility-mcp --http --port 8000

Claude Desktop / Claude Code config

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (Desktop) or ~/.claude.json (CLI):

{
  "mcpServers": {
    "ai-visibility": {
      "command": "uv",
      "args": ["--directory", "/absolute/path/to/ai-visibility-mcp", "run", "ai-visibility-mcp"]
    }
  }
}

Audit-and-fix loop

# Step 1 — audit
> audit_ai_visibility(domain="example.com")
  score: 55
  warnings:
    - "9/22 AI bots disallowed — site largely invisible to AI search"
    - "no JSON-LD structured data — LLMs lose entity grounding"
    - "no /llms.txt found at root"

# Step 2 — generate fixes
> generate_robots_patch(domain="example.com")
  → new_robots: "User-agent: GPTBot\nAllow: /\n\nUser-agent: ClaudeBot\nAllow: /\n..."
  → diff:       unified diff of exactly what changed
  → paste_target: "/robots.txt at site root, replaces existing"

> generate_json_ld(url="https://example.com/")
  → page_type_detected: "Organization"
  → script_tag: '<script type="application/ld+json">{"@context":"https://schema.org","@type":"Organization"...}</script>'
  → paste_target: "inside <head> of the page"

> generate_llms_txt(domain="example.com")
  → content: "# Example Corp\n\n> One-sentence summary...\n\n## Pages\n- [Home](...): ..."
  → paste_target: "/llms.txt"

# Step 3 — site owner pastes the three artifacts

# Step 4 — re-audit
> audit_ai_visibility(domain="example.com")
  score: 95   ← was 55

Example session

> check_ai_bot_access(domain="bandcamp.com")

  summary: { total: 22, allowed: 13, disallowed: 9 }
  warnings: ["9/22 AI bots disallowed — site largely invisible to AI search"]
  blocked:  ["GPTBot", "ClaudeBot", "Google-Extended", "Bytespider",
             "CCBot", "Meta-ExternalAgent", "FacebookBot", "Amazonbot", "Diffbot"]

> audit_ai_visibility(domain="bandcamp.com")

  score: 49
  reasons:
    -36: 9 AI bots disallowed in robots.txt
    -10: no JSON-LD structured data
    -5:  no /sitemap.xml

> check_llm_mention(brand="Anthropic", query="Who makes the leading foundation AI models?")

  share_of_voice: 0.667
  by_model:
    perplexity/sonar          mentioned=true   citations=3
    openrouter/gpt-4o-mini    mentioned=true   citations=0
    openrouter/gemini-flash   mentioned=false  citations=0
  est_total_cost_usd: 0.00088
  daily_spend_usd:    0.00088 / $5.00 cap

Security posture

This server makes outbound HTTP requests to caller-supplied domains and to LLM providers. v0.2 hardening:

  • SSRF guard. All outbound HTTP refuses loopback, link-local (AWS / GCP / Azure metadata IPs), RFC1918, CGNAT, and IPv6 ULA addresses. Redirects are re-validated.
  • Daily spend cap. LLM calls are gated by MAX_DAILY_USD (default $5.00), persisted to ~/.cache/ai-visibility-mcp/spend.json. Loop-amplification can't drain your Perplexity / OpenRouter credits.
  • Per-call cost ceiling. MAX_COST_PER_CALL (default $0.10) plus LLM_MAX_OUTPUT_TOKENS (default 1024) hard-bounds any single tool invocation.
  • No persistence of user content. Nothing is logged to disk except the daily spend totals.

Configuration

Env varDefaultPurpose
PERPLEXITY_API_KEY—Required for Perplexity models in check_llm_mention
OPENROUTER_API_KEY—Required for OpenAI / Gemini / Claude via OpenRouter
MAX_COST_PER_CALL0.10USD ceiling per tool invocation
MAX_DAILY_USD5.00USD ceiling per UTC day, persisted
LLM_MAX_OUTPUT_TOKENS1024Hard cap on output tokens per LLM call
AI_VISIBILITY_SPEND_FILE~/.cache/ai-visibility-mcp/spend.jsonOverride spend ledger location

Development

uv sync --extra dev
uv run pytest          # 40 tests
uv run ruff check .    # lint

Status

v0.3 — audit + fix loop complete. 7 tools (4 audit + 3 generator), 40/40 tests, SSRF-hardened, spend-capped. Smoke-verified against tealhq.com / bandcamp.com / anthropic.com.

License

MIT.

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