SitePulsar AEO audits: fetch FIND/READ/USE agent-readiness scores for any website.
| Endpoint | https://mcp.sitepulsar.ai/mcp (streamable-http) |
|---|---|
| Registry version | 1.0.1 |
| Now | 13 tools · grade B (85) · pin ts_59ba751612493aaaf661ded8b47c94bb · protocol 2025-11-25 |
| First / last listed | 2026-11-06 01:14 UTC / 2026-11-06 01:14 UTC |
| Grade over time | 2026-11-06: B (85), 13 tools |
Is this your server? Own a server? ToolFit hosted watch re-checks it every 24 h ($0.25 per 30 days) or 6 h ($0.60) and sends you an HMAC-signed webhook when its tools or grade change: POST https://api.youraitools.co/toolfit/v1/watch. To opt out, see About & opt-out.
Tools: check_agent_readiness run_audit get_audit get_audit_detail compare_aeo get_fixes get_audit_full search_companies probe_agent_discovery probe_ucp_readiness probe_mcp_functional scan_product_page scan_visibility
check_agent_readiness | 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. params: url* |
run_audit | 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. params: url*, target_keyword |
get_audit | 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. params: audit_id* |
get_audit_detail | 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 params: audit_id* |
compare_aeo | 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. params: urls* |
get_fixes | 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. params: audit_id* |
get_audit_full | 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 params: audit_id*, expand |
search_companies | 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 }. params: query* |
probe_agent_discovery | 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 }. params: url*, brand |
probe_ucp_readiness | 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 }. params: url*, brand |
probe_mcp_functional | 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 }. params: url*, brand |
scan_product_page | 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 }. params: url*, brand |
scan_visibility | 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 }. params: url*, brand |
Entries describe changes in tool definitions. They are not statements about a server, its quality or its author. The grade measures how the tool definitions fit model providers (token cost, schema compatibility, confusable names) as scored by the ToolFit engine at the time of the listing. JSON: append .json. Opt-out: how or hello@youraitools.co.