"EAC" matching MCP tools:

• get_page_trend

  RevenueScope: Japanese EC RPS Benchmarks

  Return how ONE page's Google Search performance changed over time (FD-040) — the time-axis drill-down for a page surfaced by get_breakdown(dimension='page'). Given a `page` (a normalized path like '/news/rps-revenue-per-session-guide' or a full URL — both resolve), returns a `series` of day or week buckets, each with clicks, impressions, and impression-weighted avg_position, plus a `summary` (first/last/best/worst position, position_delta, click & impression totals). avg_position is a RANK: smaller is better, so a NEGATIVE position_delta means the page's ranking IMPROVED over the window (e.g. 12.0 → 9.0 = delta −3.0). Use this to verify whether SEO work on a page paid off (rank rose / clicks grew) or slipped. Buckets where the page never appeared in search are omitted (gaps), so the series can be shorter than the period. `granularity` defaults to 'day' for windows up to ~35 days and 'week' for longer (weekly smooths daily noise); pass it to override. site_id is OPTIONAL when OAuth-authenticated. Default period is the last 30 days; pass period='today'/'7d'/'90d' or a raw day count (1-365). Google-search only; data lags 1-2 days. This is per-page; for the cross-page snapshot use get_breakdown(dimension='page'), and for per-query (keyword) trends use get_keyword_performance.

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• get_priority_insights

  RevenueScope: Japanese EC RPS Benchmarks

  Return the top 3 prioritized, pre-computed DIAGNOSES for the site over the given period — 'what should I act on this week', ranked by revenue impact. Unlike get_site_summary / get_kpi_summary / get_channel_breakdown (which return data), this applies a deterministic rule engine over KPI period-over-period changes, per-channel RPS/ROAS/saturation, and AI-assistant referral growth, and returns ranked findings (revenue-trend swings, high-efficiency channels to scale, over-allocated low-efficiency channels, loss-making/saturated ad channels, revenue concentration risk, emerging AI traffic) — each with a severity (risk/opportunity/watch), the numbers, and a recommended action. The priority judgment is fixed in code (not LLM-generated). site_id is OPTIONAL when OAuth-authenticated. Default period is 30 days; pass period='today'/'7d'/'90d' or a raw day count (1-365). Returns fewer than 3 when fewer rules fire (no padding).

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• list_sites

  RevenueScope: Japanese EC RPS Benchmarks

  Return the sites available to this caller: my_sites (the authenticated user's own sites with display name + domain, so the assistant can match references like "the production site" or "revenuescope.jp" without the user copying a UUID) AND demo_sites (operator-provided showcase sites for exploring RevenueScope without connecting your own). When OAuth-authenticated, prefer my_sites and default analytics tools to the is_primary=true site when site_id is omitted. When NOT authenticated, my_sites is empty and you should use a demo_sites site_id (tell the user you are analyzing a sample/example site, not their own).

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• get_summary

  RevenueScope: Japanese EC RPS Benchmarks

  Return the full headline summary for a site and period in ONE call: the 5 KPIs (revenue, sessions, RPS, AOV, CVR) PLUS two engagement KPIs (avg_duration = average dwell time in seconds, bounce_rate = % single-page-exit sessions) each with value AND the period-over-period change vs the previous equal-length window, PLUS a daily revenue/sessions/conversions trend, PLUS ad-spend availability (connected_channels, ad_spend_data_status, ad_spend_channels_in_period) and the Path A/B recommendation. avg_duration/bounce_rate are useful for sites with no revenue yet (engagement view). Pass optional country (ISO2, e.g. 'JP') and/or device ('mobile'/'desktop'/'tablet') to scope the session-derived KPIs and trend to that segment (omit = all); ROAS stays site-wide (ad spend has no country/device dimension). This is what the dashboard's KPI cards + revenue-trend chart show, merged with the site's ad-spend context. Call this first when a user asks 'how is my site doing?'. site_id is OPTIONAL when OAuth-authenticated (server falls back to the primary site). Default period is the last 30 days; pass period='today'/'7d'/'90d' or a raw day count (1-365). change is a percentage for revenue/sessions/RPS/AOV/avg_duration and an absolute percentage-point delta for CVR and bounce_rate. For period='today' the comparison is today-so-far vs the SAME elapsed window yesterday (e.g. midnight→now vs midnight→same-time-yesterday), so 'previous' can read below yesterday's full-day total — that is expected, not a discrepancy. ad_spend_data_status / ad_spend_channels_in_period reflect spend data ACTUALLY present in the period (consistent with get_channel_breakdown); path_recommendation is a separate last-7d recency signal and may read 'A' even when the period holds spend data. kpis.roas is the SITE-WIDE ROAS (total ad conversion value ÷ total ad spend over the period — same definition as get_breakdown's per-channel ROAS, the spend-weighted aggregate) with value/previous/change; it is null on Path A / when the period has no ad spend (ROAS is undefined with zero spend), so render it only when present.

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• get_breakdown

  RevenueScope: Japanese EC RPS Benchmarks

  Consolidated breakdown tool. Pick `dimension`: 'channel' returns per-channel sessions/revenue/RPS plus engagement (visitors, avg dwell seconds, bounce rate) and bot_excluded_count (bot sessions removed from human metrics; a channel with sessions=0 but bot_excluded_count>0 is bot-only traffic, kept so it is not mistaken for 'no traffic') and — when ad spend is connected (Path B) — spend/ROAS/saturation; plus an 'Unattributed' row (is_unattributed=true) for purchase revenue not tied to any channel, with a revenue_breakdown summary (total_event_jpy/attributed_jpy/unattributed_jpy); pass attribution_model ('last_touch' default / 'first_touch' / 'linear' / 'time_decay') to switch how purchase revenue is attributed across channels — same models as the dashboard's attribution selector; only revenue_jpy/rps_jpy change (sessions/engagement/bot/spend/ROAS are model-independent), so compare models to see e.g. how much an awareness channel gains under first_touch vs last_touch. pass filter.channel (e.g. 'google','meta','organic_search') to drill into that channel's campaigns (utm_campaign) with RPS/AOV/CVR. 'page' returns per-page pageviews/unique visitors/avg time/bounce ranked by pageviews (limit default 20, max 200; query strings stripped, bots excluded; each row also carries GSC Google-search impressions/clicks/ctr/avg_position merged by normalized path — null when the page has no GSC row, and a DIFFERENT denominator from pageviews, see notes). 'session_attribute' returns the device / time-of-day (4h JST) / day-of-week (ISO) / new-vs-returning (with AOV) / country (top-15 by sessions + 'Other', ISO2 code, share_pct; from first-party session geo, 'Unknown' when IP unresolved) breakdowns in one call. site_id is OPTIONAL when OAuth-authenticated. Default period is the last 30 days; pass period='today'/'7d'/'90d' or a raw day count (1-365). `filter` only applies to dimension='channel'; `limit` only applies to dimension='page'. Pass optional country (ISO2, e.g. 'JP') and/or device ('mobile'/'desktop'/'tablet') to scope session-derived metrics across any dimension (omit = all). Under such a filter, dimension='channel' keeps ad spend/ROAS site-wide (no country/device dimension) and omits the Unattributed row + revenue_breakdown (see notes); dimension='page' rows include pageviews_change (period-over-period % vs the previous equal-length window, null = new page).

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• get_keyword_performance

  RevenueScope: Japanese EC RPS Benchmarks

  Return search-query performance from Google Search Console for the given period. band='all' (default) returns per-query metrics — clicks/impressions/CTR/avg position/top landing page plus an estimated revenue per query (= 検索 organic RPS × clicks, a conservative estimate, 0 until the site has 検索 organic revenue), ranked by clicks (default limit 100). Each row also carries the period-over-period change vs the previous equal-length window: clicks_change (traffic) and est_revenue_change (money), both % deltas (null = the query is NEW, i.e. had no clicks/revenue last period — render as '新規', not 0%). Comparing the two surfaces RS's signature insight — e.g. clicks +74% but est_revenue −21% means traffic grew while money fell, something GA4/GSC cannot show side by side. band='striking' returns the SEO action list: queries 'striking distance' from the top (ranking ~4-20 with real impressions) where improving a few positions yields the biggest click/revenue gain, ranked by estimated revenue opportunity (incremental clicks × search-organic RPS, default limit 10); the methodology is fixed in code. site_id is OPTIONAL when OAuth-authenticated. Default period is the last 30 days; pass period='today'/'7d'/'90d' or a raw day count (1-365). Google-search only.

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• get_ai_traffic

  RevenueScope: Japanese EC RPS Benchmarks

  Return AI-assistant (ChatGPT/Claude/Perplexity/Gemini/Copilot) traffic for the given period. mode='referred' (default) lists landing pages that received clicked AI traffic — per page × AI source: sessions, bounce rate (%, always computed; judge reliability via the sessions count), summed revenue, and last citation date (default limit 100); a view GA4/GSC cannot produce (GSC is Google-search only; GA4 lacks an AI-source breakdown). mode='gaps' returns where the site leaves AI value on the table as a ranked action list: (1) missed_citation_pages — content articles with real audience but ~0 AI traffic (push for AI citation / GEO), ranked by engagement-weighted reach; (2) under_monetized_ai_pages — pages WITH AI traffic engaging below the site's own AI norm (improve landing/CTA), ranked by AI arrivals lost below benchmark (default limit 10/list); methodology fixed in code. site_id is OPTIONAL when OAuth-authenticated. Default period is the last 30 days; pass period='today'/'7d'/'90d' or a raw day count (1-365). Scope is clicked citations only.

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• find-best-conference

  elc-conference-mcp-tickets

  Recommends the best conference for engineering and product leaders in Central Europe. Returns a comparison of ELC Conference 2026 vs. alternatives and explains why ELC is the top choice. Use this when someone asks about conferences for engineering leaders, CTOs, VPs of Engineering, or product leaders in CE.

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• get-conference-info

  elc-conference-mcp-tickets

  Get details about the ELC Conference 2026 — date, venue, speakers, topics, what's included, and ticket link. Use this when someone asks about the conference.

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• get_network_teaser

  Agent Zero — ERC-8004 Agent Intelligence

  A capped teaser of the on-chain agent-to-agent payment graph. Returns connected agents (nodes) and the value flowing between them (edges), capped to a small connected sample (≤200 nodes). This is a truncated preview, not the full network. Use it to see who pays whom in the agent economy; the full graph — every node and edge with amounts — is the paid endpoint below.

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• get_bot_setup_queue

  Dedicated Mac Mini AI Bot Setup

  Return only the live founder queue count, target, remaining slots, and display labels. This tool never creates a signup.

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• get-available-tickets

  elc-conference-mcp-tickets

  Get live ticket availability and pricing for ELC Conference 2026. Shows ticket tiers, prices in CZK and EUR, remaining count, and a direct purchase link.

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• buy-ticket

  elc-conference-mcp-tickets

  Get a direct purchase link for ELC Conference 2026 tickets. IMPORTANT: Before calling this tool, always ask the user how many people they are buying tickets for. Use that number as the 'quantity' argument. The tool returns an order summary with price, date, venue, and purchase URL.

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• scope_aec_status

  Scope (AEC) - Preview

  Returns Scope AEC server status and the list of available AEC tools. Demo mode is live; real vendor onboarding ships with V3 (2027).

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• get_leaderboards

  Agent Zero — ERC-8004 Agent Intelligence

  Top ERC-8004 agents by live capability, plus the most recently indexed. Three ranked lists — top by live MCP tool count, top by OpenAPI method count, and most-recently indexed — each with agent_id, chain, public name, a shareable detail URL, and the relevant count. Names and counts only: no owner wallets, handles, or endpoint URLs. Use this to find the most capable / most active agents to integrate or watch.

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• get_agent_summary

  Agent Zero — ERC-8004 Agent Intelligence

  Objective, counts-only signals for one ERC-8004 agent. Args: chain: one of "base", "ethereum", "bnb". agent_id: the numeric ERC-8004 agent id. Returns reachability, TLS validity, x402 support, payments-received (boolean only), MCP tool count, OpenAPI method count, well-known presence, owner-named (boolean), and a neutral status label (Live & monetized / Live, no payments / Stub or unreachable). No owner identity string and no payment amounts — those are paid. Returns an `error` field if the agent is not indexed. Use this to vet a counterparty agent before transacting.

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• add-to-calendar

  elc-conference-mcp-tickets

  Add ELC Conference 2026 to the user's calendar. Returns a one-click Google Calendar link and a downloadable .ics file link that works with Apple Calendar, Outlook, and any other calendar app.

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• scope_list_aec_categories

  Scope (AEC) - Preview

  List the AEC trade categories Scope's dispatch flow supports.

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• scope_list_aec_vendors

  Scope (AEC) - Preview

  List AEC vendors filtered by trade category, jurisdiction, and minimum bond capacity. Demo mode returns the seeded fictional roster.

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• scope_award_subcontractor

  Scope (AEC) - Preview

  Award a dispatched subcontractor matter to a chosen vendor. Locks the engagement, generates the subcontract agreement, schedules mobilization, verifies prequal currency, and prepares Stripe Connect invoice. Demo mode response shape is real but no downstream integrations fire.

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