プラン別月額+決済手数料→損益分岐点と利益を計算 (Browser-based tool)
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568,621 tools. Updated 2026-09-14 21:37
"shopify" matching MCP tools:
- Confirm a site runs on Shopify and pull store intelligence from its public feeds — product count, price range, top vendors/categories, newest listing and a rough revenue-band heuristic. No login, no Shopify API key. — $0.01/call, x402 (USDC on base).ConnectorNo auth
- Confirm a site runs on Shopify and pull store intelligence from its public feeds — product count, price range, top vendors/categories, newest listing and a rough revenue-band heuristic. No login, no Shopify API key. — $0.01/call, x402 (USDC on base).ConnectorNo auth
- Watches a Shopify store's catalogue and returns only the products whose price or availability changed since the previous check. The first run creates the baseline and says so. — $0.05/call, x402 (USDC on base).ConnectorNo auth
- Watches a Shopify store's catalogue and returns only the products whose price or availability changed since the previous check. The first run creates the baseline and says so. — $0.05/call, x402 (USDC on base).ConnectorNo auth
- "Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.ConnectorNo auth
Matching MCP Servers
- AlicenseAqualityCmaintenanceEnables AI agents to read and write Shopify store data including products, orders, customers, inventory, and more via the Admin GraphQL API.2831 npmMIT
- AlicenseAqualityAmaintenanceA read-only MCP server that exposes the full Shopify Admin GraphQL API through 6 universal tools, with multi-store support and mutation rejection at the parser level for safety.6MIT
Matching MCP Connectors
Shopify MCP Pack — wraps the Shopify Admin REST API (2024-01)
Manage products, orders, customers, inventory, and store configuration
- Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.ConnectorNo auth
- Forward a buyer request-for-quote or engineering question to the Commonlands engineering team. Two-step, buyer-confirmed: the first call returns a preview and sends nothing; show the buyer the preview (including their reply-to email) and, only after they explicitly approve, call again with confirm: true to send. The recipient is fixed to the Commonlands inbox (the agent cannot choose it); this only sends an inquiry and never creates an order, charges a card, or writes Shopify/customer data. Include part numbers, sensor, quantity, and application when known so the team can reply with a quote. Commonlands replies by email.ConnectorNo auth
- Validate a metafield namespace and key before you define it. FREE. Shopify metafield namespaces and keys are lowercase alphanumerics and underscores; a capital letter or a dash is rejected at definition time, usually after the rest of the import has already run. Typical input {"namespace": "custom", "key": "Care-Instructions"} returns {"ok": false, "problems": ["key: dashes and capitals are not allowed"], "suggested_key": "care_instructions"}. Use when designing metafields. Not for the CSV column that carries them — that is product_csv_check. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.ConnectorNo auth
- CALL THIS FIRST to see which data sources are connected and have data. Returns connection status and record counts for: Shopify (always connected), Triple Whale, Klaviyo, Gorgias, Recharge, Google Search Console, Google Analytics, Microsoft Clarity, and YouTube. Use this to understand what data is available before making other queries. If a source shows 'not_connected', those tools will return empty results.ConnectorOAuth
- Search the Vivid Ads catalogue by product name, category, or intended use (e.g. 'corflute', 'pull up banner', 'expo', 'shopfront'). Returns matching products grounded in Vivid's own Shopify collections, so it also surfaces same-range, same-purpose alternatives — products flagged `sameRange:true` come from the top match's curated collection (returned as `collection`). ALWAYS mention these to the customer (e.g. 'we have two Pull Up Banner options, and Fabric Banner Stands do the same job'). Treat a from-price as INDICATIVE only — use vivid_product for options then vivid_price for the exact configuration.ConnectorNo auth
- Reset connector auth state for the current user. Use when tokens are stale, missing scopes, tied to the wrong account/workspace, or repeatedly failing auth. For credential-based connectors, this clears the saved credentials so the user can re-enter them. Input: connector_id (required). Supported values: google_workspace, microsoft, dropbox, shopify, shopline, quickbooks, hubspot, slack, ebay, facebook_marketing, tiktok, klaviyo, calendly, activecampaign, odoo, constantcontact, airtable, gohighlevel, monday, semrush, ahrefs, posthog, stripe, gunbroker.ConnectorDestructiveNo auth
- ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1552 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,961 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri — a resolvable pipeworx:// record URI, present only when the source emits one that resources/read can actually serve, so a citation you get back is always fetchable. "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).ConnectorNo auth
- Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) `topic` — 11 pre-mapped macro subjects ("fed", "btc", "eth", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. You do NOT have to use those exact keys: the topic is resolved through aliases and keywords, so "bitcoin", "fed rate decision", "inflation", "s&p 500" and "next pope" all land on the right subject, and `resolution.topic_matched_by` tells you whether it was an exact key, a known alias, a phrase found inside a longer question, or a single-keyword guess — treat "phrase" and "token" as a GUESS at what you meant. An unresolvable topic returns error:"mapping_failed" with mapping_stage:"topic_unrecognized" and known_topics[]; it never silently falls back to a default subject. (2) explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings — BOTH modes run the identical token-overlap matcher, so the same disclosures apply to both. `resolution` is returned in BOTH modes and says how each side's identifier was picked (which Kalshi series was queried, how many events came back, whether the chosen one had quoted markets; which Polymarket search query ran and why that event won). RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning is a sentence and compatibility_codes[] the machine-readable form; BOTH can be non-empty on returned pairs, so read them even when matched_pairs>0. Codes: event_subject_mismatch (the two event titles share no subject words — probably not the same question), temporal_mismatch (they resolve in different months), temporal_alignment_unknown (the resolution month could not be parsed on one or both sides — NOT the same as confirmed-aligned; check each event's close/strike date yourself), non_equivalent_bet_shapes, no_candidate_pairs, unclassified_legs_excluded, pairing_unverified (set in EITHER mode whenever pairs are returned: the legs were matched by keyword and word overlap, not a shared resolution source). Each entry in top_spreads_pp carries its own flags[] (temporal_mismatch, temporal_alignment_unknown, event_subject_mismatch, low_token_overlap). A leg whose metric_type or match_subtype is "unknown" is NEVER paired — those comparisons land in spread.skipped_unclassified and, when the wording lined up, in spread.low_confidence_pairs[] for inspection only. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period, in EITHER mode; null means it could not be computed (see temporal_alignment_unknown), not that the two sides align. spread.fees_note is a standing disclosure: Kalshi charges per-contract trading fees, Polymarket does not, and this tool does not model Kalshi's fee schedule — every spread_pp is gross, not a net tradeable edge. spread.resolution_source_note is the second standing disclosure: the two venues' RESOLUTION SOURCES are never compared, so a Polymarket market settling on a Binance 1-minute candle and a Kalshi event striking on Kalshi's own index at a different hour will still be shown side by side — part of any spread_pp may be a difference in contract rather than in opinion. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.ConnectorNo auth
- Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a `claim_token`; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.ConnectorNo auth
- List upcoming seller-facing deadlines on Amazon, Shopify and/or TikTok Shop, soonest first. Use for "any Amazon deadlines coming up", "what do TikTok Shop sellers need to do before month end". Deadlines come from curated official announcements (API sunsets, policy compliance dates, fee effective dates); past deadlines are excluded server-side. Free-form deadlines ("rolling") sort after dated ones. Args: platform: Optional platform slug — amazon, shopify or tiktok-shop. Empty = all platforms. Returns {generated_at, as_of, platforms, total, deadlines:[{id, platform, deadline, title, summary, effectiveAt, originalUrl, ...}]}. `as_of` is the server-side cutoff date used. Cite each record's originalUrl.ConnectorNo auth
- Calculates total landed cost per unit for a Shopify merchant importing goods. Applies 2026 regulatory surcharges (US Section 122 +10%, EU de minimis €3/item), incoterm responsibility adjustments (EXW/FOB/DDP), CIF insurance, duty and brokerage, and financial carry cost over lead time. Returns unitLandedCost, costUpliftRatio, marginErosionPct (only when unitSellingPrice is provided), full cost breakdown by layer, sensitivity drivers, risk warnings, and recommended actions. Pass baseDutyRate as a decimal (e.g. 0.12 for 12%) — surcharges are applied automatically.ConnectorNo auth
- Low-friction inventory health estimate for Shopify merchants. Use this when the merchant doesn't have precise inventory figures — requires only monthly revenue, SKU count, and industry segment. Inventory value and dead stock are estimated from industry benchmarks; all assumptions are returned transparently. Returns a 0–100 health score, risk flags, plain-language diagnosis, and prioritised recommended actions. Ideal for AI-assisted lead qualification and first-contact diagnostics. For a precise score using actual inventory figures, use inventory_health_score instead.ConnectorNo auth
- [MARKETING] Run (or fetch the cached) Agent Readiness Report for a brand's OWN store website (their Shopify or other storefront, NOT their RRG page). Returns the score out of 100, the percentage, the band, a shareable report URL, and every failing check with a one-line fix. Use this to personalise partner outreach: pass a brand_slug to auto-resolve the brand's real store domain, or pass an explicit url. Results cache for 24h, so repeat calls are instant.ConnectorNo auth
- [MARKETING] Run (or fetch the cached) Agent Readiness Report for a brand's OWN store website (their Shopify or other storefront, NOT their RRG page). Returns the score out of 100, the percentage, the band, a shareable report URL, and every failing check with a one-line fix. Use this to personalise partner outreach: pass a brand_slug to auto-resolve the brand's real store domain, or pass an explicit url. Results cache for 24h, so repeat calls are instant.ConnectorNo auth
- Hide a connector's tools from the active tool list for the current user. Use when the user says they don't use a service or wants to pause a connector, such as 'disable Shopify' or 'hide TikTok'. The connector remains configured and can be restored with enable_connector. Disabled connectors still appear in get_connector_status marked Paused.ConnectorNo auth