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470,139 tools. Updated 2026-08-21 17:54

"Diners Club" matching MCP tools:

  • Search ENS names using natural language. Supports all query types: - Filtered search: "4-letter words under 0.1 ETH" - Concept search: "ocean themed names" (semantic similarity across 3.5M indexed ENS names) - Creative search: "names for a coffee brand" (AI-generated suggestions) - Collection search: "crypto terms expiring soon" - Activity: "what sold recently?" - Availability check: "is coffee.eth taken?" - Bulk check: "check apple.eth, banana.eth, cherry.eth" - Collection/club floor: "999 club floor", "cheapest 10k club names" (returns real listings sorted by price) Returns structured results with name, price, owner, tags, and availability info. It searches the NAME database by pattern/length/price/club/vibe — it does NOT know who real-world people, teams, brands, athletes, musicians, or films are. For "find me NBA players / pop stars / Pixar films / presidents" use enumerate_entities instead (it returns correctly-spelled labels). Use this for "floor of <club>" / "cheapest in <collection>" (find_alpha can't — it has no collection param). For lifecycle-window lists — "which names are in premium / Dutch auction", "names in grace period", "expiring soon" — use get_expiring_names instead: its grace/premium statuses are on-chain-validated and premium rows carry live pricing.
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  • Validate a credit/debit card number (keyless, offline): Luhn (mod-10) checksum, detected card network (Visa/Mastercard/Amex/Discover/JCB/Diners/UnionPay/Maestro), and whether the length is valid for that network. Spaces/dashes are ignored. NOTE: this checks the number is well-formed — it does NOT verify the card is real/active/funded (that needs a payment processor).
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  • Source-verified East End events, each with its official sourceUrl and the date we last checked it. Call this for anything time-bound — tonight, this weekend, next Saturday, 'what's on in Montauk' — and never answer those from memory: a model cannot know a 2026 concert series. Dates and times are East End local (America/New_York), so 'tonight' is today's date here even if your own clock has rolled over. Read `access` before you recommend anything: it is the organiser's own gate — `sold-out` (nothing left to buy), `approval` or `invite-only` (registering is a request the host may refuse), `members-only` (club members only), `waitlist`, or `open` — and a gated room presented as bookable sends someone to a door they are not on the list for. Quote `accessNote` as written; an absent `access` means the record states nothing, which is not the same as open. Pass `town` to ask about one place; the answer tells you the total matching, whether it was truncated, and — when nothing matches — the next event there instead, which is how you say 'nothing tonight in Montauk' without guessing. `townScope.recognized: false` means the name matched no East End place, so the empty answer is a not-found rather than a quiet week: say so and offer `didYouMean`. Defaults to the next 7 days; returns up to 12.
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  • Get players available to acquire in the specified fantasy league, optionally filtered by position. This is fantasy-league availability, not professional-contract status. Pass a requested count exactly from 1 through 100; for more than 100, state the limit and ask the user to narrow the request or accept 100. Prefer the canonical fields: every response carries leagueId, seasonYear, position, count, ordering, capabilities, and ownershipScope; entries carry team (real-life club, null when none) and id (platform player id as a string, when supplied) on every platform, and ESPN entries add acquisitionState ("free_agent", "waivers", or null when the platform cannot determine the subtype) plus waiverClearsAt (ISO time); legacy platform fields remain alongside for compatibility and should not be re-explained. ownershipScope "platform_global" means percentOwned/percentStarted cover all leagues on that platform — never ownership within the selected league. An ESPN-wide started rate is never conditional on the player being rostered. Label every reported percentage as an ESPN-wide roster/start rate or Yahoo-wide market rate. Translate ownership scope silently into that provider-wide wording; never print the ownershipScope key, platform_global enum, or get_free_agents tool name. If capabilities marks rates unavailable, write "[Provider] market ownership rate: not provided"; do not print a missing response field name or null value, call get_players, or offer a lookup. When acquisitionState is null or not present, call rows "available players," never specifically free agents or waivers, and do not promise an immediate add. A returned player is already confirmed available in that league. Use get_roster only when the current request separately asks who owns a player; never offer it after an available-player result. Do not include injuryStatus or any injury detail unless the user asks for it; when asked, verify current web evidence and translate provider codes into plain language. State acquisition status in plain language from acquisitionState ("a free agent", "on waivers"); never print raw codes — neither provider codes such as FREEAGENT or WAIVERS nor canonical values like free_agent verbatim. Use current web evidence before adding analysis or pickup recommendations. Follow get_user_session then get_league_info for the selected league; fan out once per league for comparisons. Requires authentication on ESPN/Yahoo; Sleeper uses the public API. Read-only. Current date is 2026-08-21. Hard stop: after satisfying a returned-list or field-explanation request, end the answer immediately after the requested facts. Remove every closing question or offer to do more work, including roster checks, lineup-fit checks, comparisons, rankings, recommendations, role or health analysis, trends, or outlooks; never append "if you want", "tell me which player", or a similar invitation unless the user's current request explicitly asks for that additional work.
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  • Scan the ENS marketplace for alpha — names listed below their valuation. Returns ranked opportunities with a discount %, fair-value range, confidence rating, and comparable data. Candidates are selected by DESIRABILITY (real curated collections, short, accessibly priced above a floor that excludes 0.001-ETH floor-dumps), then each is precision-priced by the full Name Whisper valuation engine — the SAME engine behind get_valuation and the Value page — which is the sole judge of undervaluation. The returned fair-value range (estimatedValueEth), confidence and discountPct are the engine's own numbers, via the same cache-first path as get_valuation (with display-only signals disabled for speed), so they are authoritative and consistent with get_valuation. They are computed conservatively (the seller-wallet boost is off), so if anything they slightly UNDERSTATE fair value — report them as-is; do NOT inflate the fair value or upgrade the confidence. Use estimatedValueEth.mid as the fair-value anchor. Only opportunities the engine confirms are surfaced: a believable discount band (20%+, capped where valuations stop being reliable), MEDIUM+ confidence, and a REAL comparable-sale match (type/collection/word/entity/semantic — never a coarse same-length average). This means genuinely good, believable deals (typically 25–65% off) — not 99%-off junk. It will still surface a large discount when the engine confirms it with real comps; it just won't fabricate one. **Use this instead of search_ens_names + repeated get_valuation when the user asks for "best value", "best buy", "cheapest good name", "undervalued", "bargains", or any ranked-by-value query across multiple listings.** find_alpha does the search + engine valuation + ranking in a single call — you do NOT need to call get_valuation again on its results. If it returns fewer names than asked, the rest weren't genuine discounts vs the engine — say so rather than padding the list. Supports filters (minLength, maxLength, maxPriceEth, charType) so narrow queries like "4-letter names under 1 ETH, best value" are one call, not six. It has NO collection/category/club param. Do NOT use it for "floor price of the 999 club", "cheapest 10k-club names", or "floor of <collection>" — those name a specific collection, so use search_ens_names (which returns that collection's real listings sorted by price), or sweep if the user wants to buy the cheapest N. find_alpha is for value-ranked discovery across the market, not a named collection's floor.
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  • Returns transactions for a bank account (BANK or CREDIT type). For CREDIT (credit card) accounts, this is the ONLY way to get itemized transactions (purchases, subscriptions, etc.). Each credit card transaction MAY carry `creditCardMetadata.billId` pointing at a bill from openfinance_list_credit_card_bills, but this is a per-connector HINT, not authoritative: some connectors (e.g. Nubank) populate it sparsely (many transactions and installments arrive with no billId) or inconsistently (the same payment tagged to more than one bill). Do NOT reconstruct a bill's total by summing transactions by billId — the bill's own `totalAmount` from openfinance_list_credit_card_bills is the source of truth. CREDIT PENDING vs POSTED varies by connector: where the bank exposes future-dated `status:'PENDING'` installments, those represent the OPEN bill plus future bills (future months); where it does NOT, only the last closed bill's POSTED items appear until ~closing. Same query, different coverage per bank (upstream). To get a standardized open-bill total / total debt regardless, use openfinance_list_credit_card_bills (`open_bill` / `total_pending_debt`). Supports from/to date filters (ISO YYYY-MM-DD) and an optional keyword filter via `search_queries` (case- and accent-insensitive substring match against description and merchant name, OR semantics across multiple terms). When `search_queries` is set the tool aggregates up to 5000 transactions within from/to before filtering — narrow from/to if `truncated:true` is returned. PAGINATION: OMIT both `page` and `page_size` (the default) to get ALL transactions in the from/to range in one call — the tool auto-paginates the upstream and returns them under a single logical page (`page:1`, `totalPages:1`), up to a 5000 ceiling (`truncated:true` + warning if exceeded, then narrow from/to). Passing `page` and/or `page_size` switches to MANUAL pagination: you get one page (`page_size` items, default 50, max 500; `page` defaults to 1) with the REAL `total`/`totalPages`, so `page_size:5` alone returns the first 5 with `totalPages` telling you how many pages remain. On upstream errors, returns { total:0, results:[], warning, error } instead of throwing. `detail` controls how much per-row data you get (default `'compact'` = slim, cheap). Use `detail:'rich'` to enrich each row (when the bank connector provides it) with `merchantInfo` (estabelecimento: businessName/razão social, cnpj, cnae, category — useful for auto-classifying spending) and extra `creditCardMetadata` fields: `billId` (a per-connector HINT toward the transaction's bill — sparse/inconsistent on some connectors like Nubank, so do NOT sum by it to get a bill total; use the bill's `totalAmount` instead), `purchaseDate`, `payeeMCC`, `feeType`/`feeTypeAdditionalInfo`, `otherCreditsType`/`otherCreditsAdditionalInfo`. Use `detail:'raw'` to get the FULL untouched Pluggy transaction object (everything Pluggy returns, un-normalized — heaviest, for when you need a field we don't project). 'rich'/'raw' add tokens per row and coverage varies by bank/Open Finance, so keep the default for normal listings. For the card's statement closing/due dates use openfinance_list_accounts (`creditData.balanceCloseDate` / `balanceDueDate`). The response opens with an `account` echo block ({ account_id, bank, name, number, type, item_id }) identifying WHICH account/bank these transactions belong to. When more than one bank is connected, ALWAYS cross-check the echo against the account you intended to query and name the bank when presenting results — never attribute one bank's transactions to another. If total is 0 for a CREDIT account, check the connection health via openfinance_get_item_status — `statusDetail.creditCards.isUpdated: false` means the credit card sync failed and a force sync (openfinance_force_sync) or reconnection may be needed. May include a `provider_incident` block when the Open Finance provider has an OPEN incident affecting a connected bank: transactions may come back incomplete or wrong until the provider recovers, and reconnecting does not fix it. Bulk support: accepts account_ids for batched execution.
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Matching MCP Servers

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    Salestools Club is a technical registry and audit of 300+ sales APIs and MCP servers.
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    Provides tools for searching Sam's Club products, locating warehouse clubs, and accessing membership information using realistic mock data. It enables AI assistants to interact with product catalogs and store services for development and testing purposes.
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Matching MCP Connectors

  • Search Elron Club furnished apartments, availability, prices, details, and rental applications.

  • Connect your Sam's Club account to AI via Brazil's Open Finance: balances, statements, cards, invest

  • Forces the bank to re-sync one or more connections NOW and WAITS for it to finish (PATCH /items/:id, then polls until the item stops updating, up to ~60s). Use this when a balance or transaction list looks stale: a connection can read UPDATED yet be hours old, and this pulls fresh data WITHOUT disconnecting/reconnecting. Pass `items` as an array of selectors (item_id, connector_id, connector_name, or the user-set custom_label nickname); OMIT `items` to sync ALL linked banks. Returns `{ results, errors }`; each result has the final `status`, `executionStatus`, `lastUpdatedAt` (advances when data is refreshed), and `synced` (true = fresh data is ready). `needs_action` (e.g. MFA_REINTERACTION / LOGIN_ERROR / WAITING_USER_INPUT) means the user must re-authenticate — those results include a `reconnect_url` that opens the widget in UPDATE mode for that exact connection (user enters credentials / MFA token, data refreshes in place, no slot consumed, no disconnect needed). `timed_out: true` means the sync is still running — re-check with openfinance_get_item_status. Set `wait: false` for fire-and-forget (returns immediately while UPDATING).
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  • MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token. Best: add it to this server's config as a header `Authorization: Bearer <token>` for a permanent, non-expiring connection. Or paste it here for a session-only login: call with { token: "<jwt>" } after the user pastes, or with no args to get the link.
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  • USE THIS to check a payment card number's structure before using it — never assume a card number is valid or guess its brand. Verifies the Luhn checksum, detects the brand (Visa, Mastercard, Amex, Discover, Diners, JCB, UnionPay) from its BIN, and checks the length. Does NOT check whether the card is real, active or has funds.
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  • Floor-sweep: buy the CHEAPEST N listed ENS names in a category/collection (or matching a filter) in ONE Seaport transaction. Use this when the user wants "the cheapest N", "sweep the floor", or "buy up to X ETH of" a cohort — rather than naming specific names (that's batch_purchase). Pick the cohort with 'category' (a collection slug like "999-club") and/or 'q'/'charType'/'minLength'/'maxLength'. Bound the sweep with 'count' (how many) and/or 'maxBudgetEth' (total spend), plus an optional 'maxPriceEth' per-name cap. It selects cheapest-first across NameWhisper, OpenSea, and Grails, then packs them into one fulfillAvailableAdvancedOrders call (capped at 20 names — run again to continue). NFTs are delivered directly to the buyer; Seaport skips any order that sold since discovery and refunds the excess. The response reports what was swept (with marketplace + price), the total, and how many matched but fell outside the bound.
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  • Returns accounts for a bank connection: BANK (checking/savings) and CREDIT (credit card) with balance, number, type, subtype, bankData, and creditData. Also returns `bank` (the brand/connector name like 'Nubank Empresas' — same shown in the dashboard UI) and `connector_id`. Note: each account's `name` is the legal entity that issues the account (e.g. 'Nu Pagamentos S.A. - Instituição de Pagamento'), which is not the same as the brand — when referring to the bank in user-facing text, use `bank`. OMIT `item` to list accounts across ALL linked banks at once — the response aggregates every connection's accounts into `results`, each row tagged with its own `bank`/`connector_id`/`item_id` (use this when the user asks for 'my accounts/cards' without naming a bank). Pass `item` to target a single bank (response carries `bank`/`connector_id`/`item_id` at the root). CREDIT (credit card) `balance`: its meaning is CONNECTOR-DEPENDENT — some banks report the current open-bill partial, others the full revolving/installment debt — so do NOT treat `balance` as 'this month's bill'. The open billing cycle is defined by `creditData.balanceCloseDate` (when it closes) / `balanceDueDate` (when it's due). For a standardized open-bill amount and total debt that mean the same across connectors, use openfinance_list_credit_card_bills (`open_bill` + `total_pending_debt`, derived from PENDING transactions); closed bills come from that same tool's `results`. May include a `provider_incident` block when the Open Finance provider has an OPEN incident affecting a bank in this response: balances and credit limits may be unreliable (incomplete or wrong, e.g. a credit limit near 1,00) even with the connection UPDATED, until the provider recovers. Do not present those values as real. May include an `identity_notice` when the SAME account (same number) arrives via two connections stamped with DIFFERENT owner/taxNumber: in Open Finance those fields reflect each connection's CONSENT HOLDER (e.g. a joint account consented by both holders), so dedupe by account number before summing balances and do not attribute ownership by owner/taxNumber for those accounts. Bulk support: accepts item_ids for batched execution.
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  • Returns bill-level detail for one or more credit card bills by id (GET /bills/:id): financeCharges and payments[] (id, paymentDate, amount, valueType, paymentMode). Does NOT return individual transactions — to get itemized credit card transactions (purchases, subscriptions, etc.), use openfinance_list_transactions with the credit card account_id and a from/to date range matching the bill's billing cycle (approximately dueDate − 30d to dueDate); each transaction MAY carry a `creditCardMetadata.billId` hint toward its bill, but it's sparse/inconsistent on some connectors (e.g. Nubank), so do NOT reconstruct a bill total by summing transactions by billId — the bill's own `totalAmount` is authoritative. Pass `bill_ids` as an array — use openfinance_list_credit_card_bills first to discover ids. `{ results, errors }` batch shape. NOTE: Pluggy does NOT return a paid/status field. In Brazilian Open Finance, `payments[]` reflects payments registered during THIS bill's billing cycle — typically the payment of the PREVIOUS bill (do NOT assume this bill was paid just because `payments[]` is non-empty). To check paid status, prefer `openfinance_list_credit_card_bills` which derives `payment_status` via cross-bill match.
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  • Corrects the category of one or more transactions (PATCH /transactions/:id). Pass `items` as an array of { transaction_id, category_id } — `transaction_id` comes from openfinance_list_transactions, `category_id` from openfinance_list_categories. This overrides Pluggy's automatic categorization AND teaches Pluggy: recategorizing a transaction automatically creates a Category Rule for this client (case-insensitive exact match on the transaction's data), so FUTURE similar transactions are categorized the same way — use this to fix miscategorized transactions and improve categorization accuracy going forward. Batch shape: returns `{ updated, results: [{ transaction_id, category, categoryId }], errors: [{ id, status, message }] }` — per-item errors do not fail the whole batch.
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  • Calculate tip and split a restaurant bill among multiple people. Given a bill amount, tip percentage, and number of diners, returns the tip amount, total with tip, per-person share, and effective tip percentage. Supports rounding up to the nearest whole number for convenience. Defaults to 18% tip for 1 person. Currency-agnostic — works with any monetary unit.
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  • Search the canonical product catalog by free text (Hebrew or English), brand, category, or exact GTIN, and answer 'how much is X' for a SINGLE item. Also matches chain listing names. Send city or address and every hit comes back priced: fromPrice is the lowest it goes for at any storefront delivering there, so quote it as 'from ₪X across N storefronts' (pricedAtStorefronts) and never as one national price — there is no such thing here. pricedAtStorefronts=1 is one shop's price, not a market rate. normalizedUnitPrice is that same money per 100g/100ml/piece: compare on it, NOT on fromPrice, because a smaller pack is cheaper to buy and usually dearer per gram. Results come back cheapest per unit first. fromPrice is the ordinary price, never a loyalty-club or coupon rate. Without a location nothing can be priced and the price fields are absent. For a whole shopping list call optimize_delivery ONCE with query items — never price lines one by one here, and never add these prices up: they come from different storefronts and each carries its own delivery fee. After optimize_delivery priced the wrong product, call suggest_similar_products with the shopper's Hebrew words and the rejected product_id, then call optimize_delivery again with that product_id. Returns canonical products (not per-chain detail); call get_product for listings.
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  • Check a list of colour entries for anachronism risk. Detects whether the primary source date falls outside the requested period, whether the archive is a known modern source (RacingSilks, FootballStrips), and returns a period_relevance score and safe phrasing. Essential for historical documents: prevents a 2011 Jockey Club racing silk registration being presented as Georgian evidence. Returns anachronism_risk (none/low/medium/elevated/high), period_relevance score 0-1, safe_phrasing, and unsafe_phrasing for each entry.
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  • Consolidated cash-flow analysis for a whole bank CONNECTION over a period, in ONE call. Resolves the connection's accounts internally and fans out their transactions, so you do NOT need to call openfinance_list_accounts first nor carry account_id uuids between calls. Pass `item` (connector_id, connector_name or item_id) to target one bank, or OMIT it to analyze ALL linked banks at once. `from`/`to` are ISO dates (YYYY-MM-DD). Default `granularity:'monthly'` returns a COMPACT summary (no raw rows): total entradas, saídas, saldo_liquido, monthly evolution (`por_mes`), and `top_despesas`/`top_recebimentos` (largest N each), plus a per-account breakdown (`by_account`). Use this for 'análise anual/mensal', 'fluxo de caixa', 'entradas e saídas', 'maiores gastos/recebimentos'. Set `granularity:'raw'` to ALSO get every consolidated transaction (heavier — only when itemized rows are needed); combine with `detail:'rich'` to enrich those rows with merchantInfo (cnpj/cnae/businessName/category) + extra creditCardMetadata (billId, purchaseDate, fees), or `detail:'raw'` for the full untouched Pluggy object per row, when the connector provides them. `type` filters BANK or CREDIT accounts. On a connection with many transactions the scan caps at 5000/account and flags `truncated:true`. May include a `provider_incident` block when the Open Finance provider has an OPEN incident affecting a connected bank: the totals/rows may be incomplete or wrong until the provider recovers, and reconnecting does not fix it. Bulk support: accepts item_ids for batched execution.
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  • The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them. Covers capability requests like "find an MCP that does X", "consulta um CPF", "is there a tool for Y". Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile (every tool with its id + params, pricing, auth) so you pick the right tool_id → invoke RUNS that tool. KEY: invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit and without bloating the tool list. If the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link (the user opens it, then you retry). Use install only to make an MCP PERMANENT in the active toolkit (its tools then show up natively in future sessions); prefer invoke for a single/occasional use. list_tools lists what is callable right now. subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits. Search/describe flag installed_in_toolkit vs installed_in_workspace. Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin. It also carries the mcp.ai PROMPT LIBRARY, which is about ready-made prompt TEXT rather than MCPs: search_prompts finds one, get_prompt returns its full text with {{variables}} filled, and publish_prompt saves a prompt and returns a shareable mcp.ai/p/<slug> link that opens without login.
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  • Enumerate ENS-friendly labels for a finite real-world entity category and report which are available vs registered. USE THIS for ANY finite set of real-world people, companies, teams, or works — including queries that name a ROLE or PROFESSION rather than a league, e.g. "which tech founders have an available .eth?", "available CEOs / politicians / authors / footballers", "famous musicians I can register", "NBA hall of famers", "available Pixar films", "F1 drivers", "Beatles songs that are open". If the user is asking to find/register the names of actual real-world entities (not a vibe or an ENS club), this is the tool — even when the category sounds soft ("tech founders", "crypto founders", "famous CEOs") it is still a finite real-world list, so come straight here; do NOT fall back to search_ens_names for it. The tool generates verified, correctly-spelled ENS labels — do NOT enumerate entity names from your own context and pass them to check_availability, because models routinely misspell long-tail names (scottiepippin instead of scottiepippen) or invent people who don't exist (e.g. "johncarlton" as an NBA HOFer). This tool exists precisely to avoid that. DO NOT use this for: - Vibes / themes ("luxury watch names", "edgy crypto names") — use search_ens_names with concept_search instead. - ENS-native categories ("10k club", "3-letter words") — use search_ens_names with collection_search. - Single-name lookups — use check_availability. Returns a list of entries grouped by status. Each entry has the proper name (e.g. "Scottie Pippen") alongside the ENS label (scottiepippen.eth), so you can show users the human-readable name in your reply.
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  • Checks the LIVE operational status of the Open Finance provider (its public status page) — this is the PROVIDER's health, separate from your own connection's `openfinance_get_item_status`. Use it whenever data looks incomplete or stale even though a connection shows UPDATED (accounts/transactions/balances missing, a bank not returning everything): it reveals an upstream outage or a known incident on a specific bank/connector, so you can tell a provider-side problem apart from a connection that just needs reconnecting. Returns the global indicator (none/minor/major/critical), degraded components, open incidents, and — when you have banks connected — flags the incidents that affect YOUR connected banks in `your_banks_affected`.
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