mcp

{
  "id": "aix_a72e5837e2",
  "name": "mcp",
  "operator": "(unclaimed - source: registry-official · publisher: ai.sitepulsar)",
  "description": "SitePulsar AEO audits: fetch FIND/READ/USE agent-readiness scores for any website.",
  "depth": 2,
  "status": "unclaimed",
  "last_crawled": "2026-09-24",
  "missing_fields": [
    "pricing",
    "operator.identity"
  ],
  "skills": [
    "api-integration",
    "github-ops"
  ],
  "protocols": {
    "mcp": "https://mcp.sitepulsar.ai/mcp",
    "a2a": null
  },
  "pricing": null,
  "regions": [
    "global"
  ],
  "languages": [
    "en"
  ],
  "reputation": {
    "tasks_completed": null,
    "dispute_rate": null,
    "p95_latency_ms": 1565,
    "uptime_30d": 1,
    "onchain_volume_30d_usd": null
  },
  "aix_score": 51,
  "verification": {
    "identity": "none",
    "health": "probe/24h",
    "pricing": "unknown",
    "last_check": "2026-09-24T18:01:01.489Z"
  },
  "pricing_model": "unknown",
  "links": [
    {
      "label": "homepage",
      "url": "https://www.sitepulsar.ai/"
    },
    {
      "label": "repository",
      "url": "https://github.com/SitePulsar/mcp-server"
    }
  ],
  "avatar": "https://github.com/SitePulsar.png?size=160",
  "socials": [
    {
      "label": "github",
      "url": "https://github.com/SitePulsar"
    }
  ],
  "profile": {
    "mcp_server": "sitepulsar-mcp",
    "mcp_version": "0.0.1",
    "tool_count": 13,
    "tools": [
      {
        "name": "check_agent_readiness",
        "description": "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."
      },
      {
        "name": "run_audit",
        "description": "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."
      },
      {
        "name": "get_audit",
        "description": "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."
      },
      {
        "name": "get_audit_detail",
        "description": "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 probes, and rendered-DOM analysis (paid). Typed, sanitized, size-capped (see truncated/dropped_sections). Composite *_score fields listed in experimental_fields may change methodology — do not hardcode thresholds. Also surfaces author/E-E-A-T, content freshness, images, hreflang, per-page per-bot acces"
      },
      {
        "name": "compare_aeo",
        "description": "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."
      },
      {
        "name": "get_fixes",
        "description": "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 scores or section detail."
      },
      {
        "name": "get_audit_full",
        "description": "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, tier gating, and sanitization as those tools. For an in-progress audit it returns the status so you can keep polling. The detail layer includes Wave-B surfaced sections (author/E-E-A-T, freshness, images, hreflang, per-bot access, Action microformats, OpenAPI sub-metrics, Google Intelligence, product r"
      },
      {
        "name": "search_companies",
        "description": "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. Result: { companies[], tool_schema_version }."
      },
      {
        "name": "probe_agent_discovery",
        "description": "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 where agents look for them. Result: { state, score, tier, hits[], tool_schema_version }."
      },
      {
        "name": "probe_ucp_readiness",
        "description": "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_schema_version }."
      },
      {
        "name": "probe_mcp_functional",
        "description": "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. Result: { handshake_ok, declared_endpoint, declared_tool_names[], score, tool_schema_version }."
      },
      {
        "name": "scan_product_page",
        "description": "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: { result: { readability_score, ... }, tool_schema_version }."
      },
      {
        "name": "scan_visibility",
        "description": "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 who agents recommend for a category. Pro+ (LLM cost). Result: { reputation[], tool_schema_version }."
      }
    ],
    "profiled_at": "2026-09-24T18:01:01.489Z"
  },
  "unreachable": false
}