MCP server

Sitepulsar Official

ai.sitepulsar/mcp

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

SitePulsar AEO audits: fetch FIND/READ/USE agent-readiness scores for any website.

Website Source

At a glance

Type

MCP server

Publisher

sitepulsar.ai (verified by the MCP Registry)

Status

Working at last check

Tools

13

Token cost

About 2,800 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http sitepulsar https://mcp.sitepulsar.ai/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.sitepulsar]
url = "https://mcp.sitepulsar.ai/mcp"

Gemini CLI

{"mcpServers":{"sitepulsar":{"httpUrl":"https://mcp.sitepulsar.ai/mcp"}}}

Cursor

{"mcpServers":{"sitepulsar":{"url":"https://mcp.sitepulsar.ai/mcp"}}}

VS Code

{"servers":{"sitepulsar":{"type":"http","url":"https://mcp.sitepulsar.ai/mcp"}}}

Antigravity

agy mcp add sitepulsar https://mcp.sitepulsar.ai/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"sitepulsar","server_url":"https://mcp.sitepulsar.ai/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"sitepulsar","server_url":"https://mcp.sitepulsar.ai/mcp"}

Tools

• check_agent_readiness ~144 tokens
  Fast synchronous AEO / agent-readiness read of a single URL: robots and bot access, structured data (schema), and content structure. Returns immediate signals without running a full audit. Use this to triage a page or sanity-check before deciding whether the heavier run_audit is worth a credit.
• compare_aeo ~141 tokens
  Compare AEO posture across multiple URLs (e.g. a brand versus its competitors) on the same FIND/READ/USE pillar scale. Async: returns an audit_id to poll with get_audit. Spends credits only for freshly-audited URLs; recent audits are reused uncharged.
• get_audit ~156 tokens
  Fetch an audit's status and, when complete, a compact decision-ready SUMMARY: AEO score (overall + FIND/READ/USE), a short summary, the weakest pillar, headline takeaways, and the top fixes. Lead with this; call get_audit_detail only when you need the full per-section breakdown.
• get_audit_detail ~512 tokens
  Full structured per-section breakdown of a completed audit, on demand (only call after get_audit when you need depth): per-dimension FIND/READ/USE sub-scores, reputation across AI engines, competitor cluster (named for paid tiers), crawl/schema/robots findings, agentic-readiness + USE functional pro
• get_audit_full ~334 tokens
  One call that returns a completed audit's SUMMARY, full per-section DETAIL, and deduplicated prioritized FIXES together — so you don't have to chain get_audit → get_audit_detail → get_fixes. Use `expand` to trim the payload ('summary' | 'detail' | 'fixes' | 'all'; default 'all'). Same ownership, tie
• get_fixes ~168 tokens
  Return the prioritized, pillar-tagged (FIND / READ / USE) action plan for a completed audit, deduplicated across sources, with machine-actionable implementation steps included on fixes where available. Use this when you want the to-do list to act on (or hand to a coding agent), rather than the score
• probe_agent_discovery ~210 tokens
  Checks selected registries (official MCP registry, PyPI, GitHub) for packages/servers tied to a domain or brand. A discovery-surface check (can agents find your published tooling?), not a visibility check. Use when you want to know whether a brand has discoverable agent/developer artifacts listed wh
• probe_mcp_functional ~211 tokens
  Discovers a site's advertised MCP endpoint (mcp.json / .well-known) and inspects its *declared* OAuth/transport posture (advertised, not guaranteed-working — it does not run a full live handshake). Use when checking whether a site exposes a connectable MCP server and what it claims to support. Resul
• probe_ucp_readiness ~188 tokens
  Inspects /.well-known/ucp to report whether AI shopping agents can transact with the site (presence + advertised capabilities only — never a live purchase). Use when evaluating an e-commerce or merchant site for agentic-commerce readiness. Result: { has_ucp_profile, capabilities[], score, tool_schem
• run_audit ~160 tokens
  Run a full AEO audit of a URL covering FIND, READ, and USE. Async: returns an audit_id to poll with get_audit. Accepts an optional target_keyword. Spends one audit credit per fresh run; a same-URL re-run within 24h reuses the cached audit, uncharged.
• scan_product_page ~200 tokens
  Deterministically scores one product page (schema, price, availability, image) 0–100 for shopping-agent readability — no LLM, fully repeatable. Use when you want a precise, single-page readability score for a specific product URL rather than a whole-site audit. Available on Pro+ plans. Result: { res
• scan_visibility ~212 tokens
  Live AI-visibility scan for a brand: crawl + reputation sampled across AI engines, returning where *that* brand is mentioned (any public brand, not just your own). Use when you want to know whether and how a named brand already surfaces in AI answers — complementary to search_companies, which finds
• search_companies ~164 tokens
  Samples the major AI engines for which companies they name for a query (e.g. "best CRM for startups"); returns a consensus shortlist (≤5). Use when you want to know who agents *recommend* for a category — not where a specific brand is mentioned (use scan_visibility for that). Free, no URL needed. Re

Browse

• GitHub tools
• OpenAPI tools
• Web scraping
• Website monitoring
• To-do lists
• CRM

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