Agent-first product listing: JSON catalog, agent card, MCP door, hops, measured landings (Agent Ads). 7-day trial, founding $50/mo (first 10, 12 mo) then $100/mo. Follow start_here.hop first (302). Task text discarded.
ConnectorNo auth
614,227 tools. Updated 2026-09-26 19:09
"FIRST" matching MCP tools:
- Win probability for the side batting first in a men's T20, while the total is being set. On 106 men's T20 internationals played after all its training data (1 Jul to 17 Sep 2026): AUC 0.912 with both team names and the ground, 0.888 with the ground only. Per call.ConnectorNo auth
- First N Lines: First N LinesConnectorNo auth
- Remove First Word: Remove First WordConnectorNo auth
- 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.ConnectorNo auth
- Return a content 'playbook' for the site: every content page classified into ONE of five action buckets over a weekly-style window comparison (current window vs the immediately preceding window of equal length), ranked by search-opportunity × session gain so you can tell the user which page to GROW next and what to do: within the 'striking' bucket rows are ordered by expected_sessions_gain DESC (the band-CTR headroom that is the actionable lever there), while the other buckets keep real landing revenue DESC (largest revenue at stake first). This surfaces search intent to add sessions (grow the traffic denominator), NOT CVR — a page already winning on sessions/revenue but with zero clicks still shows up. Buckets: 'decaying' (search clicks actually fell, OR the page had real traffic (previous clicks ≥3) and its rank slid ≥2 positions from within the click zone while clicks did NOT grow → refresh/rewrite; a rank slide alone with growing/negligible clicks is NOT decay — search clicks are the primary signal, position only a leading indicator), 'striking' (has striking-distance queries at positions 4-20 with click upside but clicks still low → push those queries up; top 3 listed in striking_queries), 'rising' (clicks grew significantly → produce more of this, strengthen CTA), 'dormant' (has impressions but ~0 clicks and its main query is far below the click zone → big rewrite or consolidate; zero-pageview pure-rank pages surface here), 'stable' (none of the above → watch). Each page also carries current/previous clicks·impressions·avg_position, is_new, landing sessions/engaged/revenue_jpy, AI-referred sessions/revenue/sources, expected_sessions_gain (the window's expected incremental sessions from striking-band queries — a search click is ~1 session, so it is NOT re-converted via CTR; normalize to a monthly figure with the window length), and expected_revenue_gain (expected_sessions_gain × page RPS, returned ONLY when revenue>0 and sessions>=5 — display-only projection, never a sort key). The deterministic action mapping and all (provisional) thresholds come back in `criteria`; the model does the narrative interpretation (mcp-first). Rows with confidence='low' carry `caveats` — 'geo_winning_suspect' (AI Overview/citations likely substitute the click: a GEO win, don't break the page; cross-check get_ai_traffic), 'zero_click_suspect' (SERP-feature occupation or intent-mismatch/polysemous query: verify the live SERP first), 'ai_cited' (decaying but the AI citation is alive) — verify before acting on low-confidence rows; definitions in criteria.caveat_flags. The response is summary-first (token-aware): `bucket_summary` always holds the FULL pre-limit distribution (per-bucket count/revenue/clicks) plus `total_pages`, while `pages` returns only the top rows in priority order (default limit 15, max 200); pass bucket='striking' etc. to drill into one bucket, and check `truncated` — when present it tells how many rows were cut and how to fetch them. GSC-driven and Google-search only; data lags 1-2 days so the current window's right edge sits a few days back. When narrating a bucket to the user, scope it to Google search — say 'search traffic to this page is declining', NOT 'this page is declining'; the classification is a search-trend diagnosis, not overall page health, so a page labeled 'decaying' can be thriving on Direct/social/AI. Before calling a negative bucket (decaying/dormant) a problem, cross-check the row's landing sessions/revenue_jpy and ai_sessions. site_id is OPTIONAL when OAuth-authenticated. Default window is the last 7 days vs the prior 7; pass period='30d'/'90d' or a raw day count (2-365). Window date bounds are INCLUSIVE on both ends, so period=Nd actually spans N+1 calendar dates (the real range is in `window`); both windows share the same length, so the comparison stays symmetric. This is the cross-page action snapshot; for one page's time series use get_page_trend, and for AI-citation gaps use get_ai_traffic(mode='gaps').ConnectorNo auth
Matching MCP Servers
- AlicenseAqualityDmaintenanceA curriculum that teaches AI agents how to spend their own money. Sixteen lessons from "what is a wallet" to your first x402 purchase. Teacher, not butler — never signs, pays, or holds keys.1929 npmMIT
- AlicenseAqualityDmaintenanceLong AI conversations fail in predictable ways. Context-First fixes all four: Failure Mode What Goes Wrong Context-First Solution Context Drift AI forgets earlier decisions and intent as the conversation grows context_loop + detect_drift continuously re-anchor every turn Silent Contradiction New inputs silently overrule established facts — the AI doesn't notice detect_conflicts compares every inp81MIT
Matching MCP Connectors
Base wallet-agent beta: deposit 1 USDC; PASS returns 1 USDC; terminal failure is refunded.
Human $1 Stripe checkout and $0.05 Base USDC agent verify over HTTP 402. Self-pay rejected.
- Return the latest competitor SEO snapshot for the site (FD-041): which keywords each tracked competitor DOMAIN ranks for on Google (Japan/ja), at what position, with monthly search_volume, cpc and etv (estimated monthly traffic — a visit estimate, not a monetary value), plus how each rank moved vs the previous snapshot. READ-ONLY — this tool never runs a research (that costs money and is triggered separately from the dashboard, the competitor-research Edge Function); it only reads what was already fetched. The response is summary-first (token-aware): each domain carries a constant-size `summary` (total_keywords, total_etv, volume_bands and rank_bands histograms, and vs_previous new/lost/improved/declined/same counts) that always reflects the FULL keyword set, while `keywords` returns only the top rows ranked by `sort` (etv default | volume | rank; default limit 10 per domain, max 100) with a `truncated` block (shown/matching_total/lost_total). rank is a POSITION: smaller is better, so a NEGATIVE rank_delta means the competitor's ranking IMPROVED (change ∈ new/improved/declined/same/unknown). Keywords the competitor ranked for before but lost are disclosed in `lost_keywords` (top 10 by previous etv), never dropped silently. Pass `domain` to focus one competitor, `min_volume` to drop low-volume keywords. When the site has NO completed research yet the response is { researched:false } with a `guidance` string explaining a research must be triggered from the dashboard first — this tool cannot start one. site_id is OPTIONAL when OAuth-authenticated. This is the external competitor lens (third-party SERP data); for YOUR OWN search performance use get_keyword_performance, and for your content playbook use get_content_actions.ConnectorNo auth
- Hepburn romanize Japanese names (katakana/hiragana) in passport style. Supports family-first and given-first order. 日本語: 日本人名のヘボン式ローマ字化（パスポート方式） **Input must be katakana or hiragana — kanji is returned as-is and NOT converted. To get readings of kanji names, call kanji.toKana first.**ConnectorNo auth
- [free] Describe this connector: flagship-first tools layer (search/answer as the front door), how to install (Claude Code / Cursor / npm), free vs paid tiers, and discovery URLs. Call this first.ConnectorNo auth
- Tennis season first-serve-won leaderboard: Share of first-serve points won per player, from real match-stats aggregates, ordered highest pct first. When to use: - Share of first-serve points won per player, from real match-stats aggregates, ordered highest pct first. season tables; clutch/serve-efficiency leader queries. Prefer over: raw leaderboard via call_api for agent-normalized rows. Do not use when: ranking position → standings with game tennis; week-over-week movement → rankings_movers; one player's recent form → player_form. Tennis-only. Season defaults to 2026; tour (ATP|WTA) is optional — omit it for the combined board. Only players with at least 300 first serves in qualify. Parallel-safe: yes. Upstream cost: 1.ConnectorNo auth
- Tennis season comeback-wins leaderboard: Share of matches won after losing the first set per player, from real first-set rows joined to completed matches, ordered highest pct first. When to use: - Share of matches won after losing the first set per player, from real first-set rows joined to completed matches, ordered highest pct first. season tables; clutch/serve-efficiency leader queries. Prefer over: raw leaderboard via call_api for agent-normalized rows. Do not use when: ranking position → standings with game tennis; week-over-week movement → rankings_movers; one player's recent form → player_form. Tennis-only. Season defaults to 2026; tour (ATP|WTA) is optional — omit it for the combined board. Only players with first-set data on at least 20 matches qualify. Parallel-safe: yes. Upstream cost: 1.ConnectorNo auth
- Pull down the notification panel, the Quick Settings panel, or collapse open panels. action="notifications": pull down the first panel (notifications). action="settings": pull down Quick Settings (some OEMs require notifications first). action="collapse": close any open panel. Tries control channel first; falls back to `cmd statusbar` shell on error. Returns { ok, action, transport }.ConnectorOAuth
- List first-hand English climbing-route guides on Spaghetti and Summits. Returns each route's name and the URL of the guide on the blog. Call this when the user asks what climbing routes are on the site, or needs a link to a route page.ConnectorNo auth
- Live goal state, ledger summary, and checkout URLs. Open bounty: third-party human ≥$1 Stripe plus non-owner agent x402 verify ($0.05+ USDC Base). Free — call before verify. See bountyManifestUrl in response.ConnectorNo auth
- Hepburn romanize Japanese names (katakana/hiragana) in passport style. Supports family-first and given-first order. 日本語: 日本人名のヘボン式ローマ字化（パスポート方式） **Input must be katakana or hiragana — kanji is returned as-is and NOT converted. To get readings of kanji names, call kanji.toKana first.** [Torify namespace — official]ConnectorNo auth
- Pay Fieldproof $42. Returns every live rail: Stripe card_uri, EIP-681 usdc_uri, BIP-21 btc_uri, x402 POST /v1/sponsor, Zelle, and GET /v1/invoice. One settlement meets the first-$42 bar.ConnectorNo auth
- Get first-half / first-five / first-set lines and live progress for an NFL, NCAAF, NBA, NCAAB, MLB, soccer, or tennis event. Joins persisted first_half_spreads / first_half_totals mains to this-event period scores (1H = Q1+Q2, NCAAB or soccer native 1H; MLB F5 = innings 1–5; tennis S1 = first-set games) and grades the period, not the full game. GET /odds / get_odds stay on moneyline/spread/total. Returns available:false with no charge if no period mains have been ingested. Other sports return HTTP 400.ConnectorAPI key
- Get deduplicated creative count, first-discovered creative count and ad-plan count for one game, platform and explicit date range (maximum 180 days). Creative count uses lifetime overlap; first-discovered count uses first appearance within the range. No paging is needed. Always use this tool for platform totals rather than counting pages from discovery tools.ConnectorNo auth
- Arc Sniper Watch: new Uniswap v4 pools on Arc in the last 24 h, who bought each first and how many seconds after it opened, whether the first buyer sold straight back, USDC depth, flags with reasons, and a leaderboard of the fastest first buyers. Read from PoolManager events every five minutes. Free.ConnectorNo auth
- Arc Sniper Watch: new Uniswap v4 pools on Arc in the last 24 h, who bought each first and how many seconds after it opened, whether the first buyer sold straight back, USDC depth, flags with reasons, and a leaderboard of the fastest first buyers. Read from PoolManager events every five minutes. Free.ConnectorNo auth
- Alias for post_task. Use when the agent should stop guessing and hire a human. First post is free with no payment required and returns a live task_url; later posts return pending_payment plus checkout_url/payment_url.ConnectorNo auth