krissanders/ai-visibility-mcp
FreeNot checkedAudit how AI sees your website. Per-bot robots.txt verdicts for 22 known AI user-agents (GPTBot, ClaudeBot, PerplexityBot, Google-Extended, Bytespider, etc), Cl
About
Audit how AI sees your website. Per-bot robots.txt verdicts for 22 known AI user-agents (GPTBot, ClaudeBot, PerplexityBot, Google-Extended, Bytespider, etc), Cloudflare AI-default flags, on-page schema, sitemap, llms.txt, SPA-shell detection, and cross-model brand mentions via Perplexity + OpenRouter. 0-100 score with explainable deductions; parallel competitor compare. SSRF-guarded, per-call and daily LLM spend caps. MIT, 24 tests, stdio + HTTP.
README
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.
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:
- Audit — find what's blocking AI visibility
- Fix — generate the artifact that corrects it
- Paste — site owner applies the output
- Re-audit — verify the fix was picked up
Tools
Audit tools
| Tool | Purpose | Needs API keys? |
|---|---|---|
check_ai_bot_access(domain) |
Per-bot robots.txt + Cloudflare AI-default flag for 22 AI user-agents | No |
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 flight | No |
Generator tools (v0.3)
| Tool | Purpose | LLM call? |
|---|---|---|
generate_robots_patch(domain, allow_bots?, deny_bots?) |
Corrected robots.txt that opens access to AI bots; preserves existing rules; detects Cloudflare | No |
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 fields | Yes (gpt-4o-mini) |
generate_llms_txt(domain, crawl_depth?, max_pages?) |
spec-compliant llms.txt; crawls homepage + sitemap; graceful fallback to link extraction | Yes (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) plusLLM_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 var | Default | Purpose |
|---|---|---|
PERPLEXITY_API_KEY |
— | Required for Perplexity models in check_llm_mention |
OPENROUTER_API_KEY |
— | Required for OpenAI / Gemini / Claude via OpenRouter |
MAX_COST_PER_CALL |
0.10 |
USD ceiling per tool invocation |
MAX_DAILY_USD |
5.00 |
USD ceiling per UTC day, persisted |
LLM_MAX_OUTPUT_TOKENS |
1024 |
Hard cap on output tokens per LLM call |
AI_VISIBILITY_SPEND_FILE |
~/.cache/ai-visibility-mcp/spend.json |
Override 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.
Install krissanders/ai-visibility-mcp in Claude Desktop, Claude Code & Cursor
unyly install krissanders-ai-visibility-mcpInstalls into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.
First time? Get the CLI: curl -fsSL https://unyly.org/install | sh
Or configure manually
Run in your terminal:
claude mcp add krissanders-ai-visibility-mcp -- uvx --from git+https://github.com/krissanders/ai-visibility-mcp ai-visibility-mcpFAQ
Is krissanders/ai-visibility-mcp MCP free?
Yes, krissanders/ai-visibility-mcp MCP is free — one-click install via Unyly at no cost.
Does krissanders/ai-visibility-mcp need an API key?
No, krissanders/ai-visibility-mcp runs without API keys or environment variables.
Is krissanders/ai-visibility-mcp hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install krissanders/ai-visibility-mcp in Claude Desktop, Claude Code or Cursor?
Open krissanders/ai-visibility-mcp on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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