"Trade-In Value Estimator for Canada" matching MCP tools:

• tracepass_passport_fieldsA

  TracePassA

  Update field values on a Digital Product Passport. Every change is recorded in the passport's audit trail with the credential that made it (API key or connected app) and this MCP channel. `source` (optional) says where the value came from. Omit it, or pass "manual", when the user gave you the value or it comes from their own records: it is written with the user's rights (approved for an API key or an admin; sent to review for a connected app acting for an editor). Pass "ai_suggested" when you found or inferred the value yourself (web research, reading a document): it lands in the dashboard review queue for a human to approve, and it is refused on fields only the economic operator may state or that must be measured (e.g. battery stateOfHealth). Actions (pass via `action`, with `args`): - update — args: { id, fieldKey, value, source? }. `value` type matches the field's dataType (string, number, boolean, array, object). - update_by_serial — args: { serial, fieldKey, value, gtin?, source? }. Same as update, addressed by your own serial. A serial is unique only WITHIN a GTIN — if it isn't unique in your account the call returns 409 ambiguous_serial; pass `gtin` (or use update by id) to resolve exactly.

  Connector

  Destructive

  No auth

• estimate_lead_timeA

  Silicon AnalystsA

  Heuristic chip manufacturing LEAD TIME estimator (MANUFACTURING CYCLE TIME). Given total mask layers (or a processNode to default them), foundry utilization % (optional — defaults from live foundry-allocation data), and packagingType, returns min/max bands: fabDays, fabWeeks, packagingWeeks, totalWeeks, plus effectiveDpml (days per mask layer), the operating-curve weight, a resolved-inputs echo, assumptions, methodology, and public-source citations. USE THIS for: "how long to manufacture this chip" — wafer-fab cycle time + packaging assembly/test time for hypothetical chips; cycle-time sensitivity to fab utilization or packaging class (conventional vs flip-chip vs CoWoS). DO NOT USE for: booking windows / allocation lead time — how long until a booked-out foundry STARTS wafers, publicly 52–156+ weeks at N3-class nodes and CoWoS (use get_foundry_allocation); chip cost (use calculate_chip_cost / get_accelerator_costs). Provide maskLayers (integer 10–200) or processNode (tsmc-n3 | tsmc-n5 | tsmc-n7 | tsmc-n16 | tsmc-28 | samsung-3nm | samsung-5nm | samsung-7nm | samsung-14nm | intel-7 | intel-16 | gf-12lp | gf-fdx | umc-22-28 | umc-40 | smic-28). packagingType accepts coarse classes (conventional | flip-chip | cowos, default flip-chip) or any platform packaging id (fc-bga, wirebond-bga, cowos-l, copos, ...). Utilization ≤80% settles at the best-case band; ≥95% converges to the worst-case bound (FabTime operating-curve shape). Heuristic from public DPML benchmarks — directional, confidence LOW, not a foundry quote. Cite as "Silicon Analysts — Lead Time Estimator".

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• query_ai_infrastructure_trade_v1A

  exascale.buildA

  Query verified U.S. monthly IMPORTS of integrated circuits (HS-8542) — customs value (USD) by country of origin — from the U.S. Census Bureau's International Trade data. Use this for "how much $ of chips did the US import (from Taiwan / South Korea / in total) and how is it trending" questions. HS-8542 is ALL integrated circuits (processors, memory, amplifiers, parts) — NOT AI-accelerator / GPU-specific. Filter by `country` (the verbatim Census name, e.g. "TAIWAN", "KOREA, SOUTH"), `cty_code` (the Census country code, e.g. "5830"), `country_level` ("total" = the all-countries TOTAL, "country" = an individual country, "grouping" = a Census bloc/continent like ASIA / APEC / EU), `year`, `data_month` (one month, ISO first-of-month e.g. "2026-04-01") or the `data_month_from`/`data_month_to` range. Group by any of `country`, `cty_code`, `country_level`, `data_month`, or `year`. Pass each parameter as a top-level key of `params` (flat — not nested under a `filter`, `filters`, or `where` key). Example: `{"country_level": "country", "group_by": ["country"], "order_by": "general_value_usd", "top_n": 5}` for the top source countries; `{"country_level": "total", "group_by": ["data_month"]}` for the national trend. Returns JSON aggregates with citations and optional row-level records when `include_records` is true — every value cites the exact Census response row, re-verifiable via get_source_evidence_v1. Measures: `general_value_usd` (general imports value) and `consumption_value_usd` (imports for consumption) — value only; HS-8542 reports no meaningful quantity at this level, so there is no chip count. NEVER SUM across country rows: Census's groupings (ASIA, APEC, EU, OECD, ASEAN, the continents) OVERLAP each other and the individual countries, and the all-countries TOTAL contains everything — so adding rows double-counts. Filter `country_level=total` for the U.S. national figure, `country_level=country` for individual countries, or group_by country for the per-country series; a cross-row sum returns a country_aggregation note and nulls the metric in ranking remainders. Country is the country of ORIGIN (Census attribution), not where a chip is installed — there is no U.S. state/county breakdown. Imports only (not exports), customs value (not landed/CIF/duty), and recent months are preliminary and revised in later releases.

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• scan_slateA

  infersportsA

  Scan today's whole slate in ONE call — each fixture with honest status + value/arb signal. The batch alternative to looping find_match → get_sharp_line per match. Returns every fixture in the filter with its status (finished is excluded from "live"), live score/clock, and a pre-computed value/arb signal; value/arb matches are sorted to the top and the list is truncated to ``limit`` (so truncation drops the quiet ones). Line movement is NOT included (that needs the opening lookup) — drill into a single fixture with get_opening_line. DETECTION ONLY / read-only. Args: sport: optional filter — "football" or "basketball". status: optional filter — "live" | "scheduled" | "finished". league: optional league filter — a name (fuzzy-matched, e.g. "World Cup") or an external id (lg_…). markets: optional — limit the value/arb scan to "1x2"/"asian_handicap"/"totals" (default all). period: optional — "full_time" or "half_time" (default both). min_edge_pct: value threshold for the per-match signal (default 1.0). min_margin_pct: arbitrage threshold for the per-match signal (default 0.0). only_signal: if true, return only fixtures that have a value or arb signal. format: odds format — decimal | hk | malay | american | indonesian | probability. limit: max entries to return, signal-first (default 20, max 100).

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• keyword_researchA

  AMZ VaultA

  Keyword Research (marketplace term universe): search the FULL Top Search Terms store by phrase - not anchored to any ASIN. Filters: contains (up to 5 substrings, ANDed), department, rank_max, min_volume; period WEEK or MONTH (MONTH = monthly volumes); sort rank | volume | trend. Each term: search_frequency_rank, volume (amazon_sqp = TRUE Amazon volume where any account's SQP covers the term; estimated_from_rank with volume_band otherwise), rank_change vs ~4 periods back, and the top-3 clicked ASINs with click/conversion shares (the term's competitive landscape). The estimator block reports calibration health (pairs, typical error factor, band coverage). Use keyword_finder for ASIN-anchored lookups; this tool for term-first research. For the guided process start with keyword_opportunities.

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• void_tradeA

  mcpA

  [JOURNAL] Void a mis-logged journal trade by trade_id (wrong asset, duplicate, fat-finger) with an optional reason. Soft-delete: the trade is removed from your stats and the default journal view but retained and recoverable (get_journal status='void' lists voided trades). Voiding a CLOSED trade removes its outcome from your calibration — disclosed in the response. Use this for entries that never should have existed; use close_trade for real trades that ended. Pro.

  Connector

  Destructive

  No auth

• estimate_urlsA

  UnphurlA

  Pre-flight credit estimator for a list of URLs. Returns counts + credit estimate. Free, no credits consumed. Call this before check_urls to show the user how many credits the batch will cost. Classifies each URL against three free gates: - tranco: URL's registrable domain is in the Tranco top 100K (trusted, treated as clean with score 0, no pipeline needed) - cached: URL's hostname is already in Unphurl's reputation cache (results available, no pipeline needed) - unknown: URL needs full pipeline analysis (costs 1 credit per URL) Returns counts for each gate plus total, credits_needed, credits_min, and credits_max. credits_min and credits_max are both equal to the unknown count in the current implementation. Maximum 500 URLs per call. Rate limit: 10 requests per minute. Does not follow redirects; classifies each URL as submitted. Typical agent flow: 1. Collect a list of URLs 2. Call estimate_urls to get the cost breakdown 3. Show the user the breakdown and ask for approval 4. On approval, call check_urls on the unknowns only

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• get_rate_benchmarkA

  TempGuru Event StaffingA

  The TempGuru Event Staffing Rate Index: all-inclusive W-2 hourly bill rates by role from 407 measured US/Canada markets, as a typical rate plus the full national range (brand ambassadors shown by market tier), with methodology and a ready-to-use citation line. Perfect for 'What do event staff cost in 2026?', 'Industry benchmark for brand ambassador rates?', or any article, report, or comparison that needs citable staffing-rate data. DO NOT use for one city's price (use get_role_pricing) or to build an event budget (use plan_staffing). <examples>get_rate_benchmark() ; get_rate_benchmark(role='brand-ambassadors') ; get_rate_benchmark(tier='hub')</examples> <hints>Returns a national typical + range per role; brand ambassadors by tier. Pass tier to add each role's measured span within that tier (tier_usd). For one city's exact rate use get_role_pricing. Cite as: TempGuru Event Staffing Rate Index 2026, tempguru.co.</hints>

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• void_tradeA

  n0brainsA

  [JOURNAL] Void a mis-logged journal trade by trade_id (wrong asset, duplicate, fat-finger) with an optional reason. Soft-delete: the trade is removed from your stats and the default journal view but retained and recoverable (get_journal status='void' lists voided trades). Voiding a CLOSED trade removes its outcome from your calibration — disclosed in the response. Use this for entries that never should have existed; use close_trade for real trades that ended. Pro.

  Connector

  Destructive

  No auth

• get_congress_tradesA

  ko-mcpA

  Search individual stock trades disclosed by U.S. Congress members (House and Senate) under the STOCK Act. Returns a markdown table of transactions: member name, chamber, ticker, buy/sell type, transaction date, disclosure date (the gap between the two reveals reporting delay), dollar amount range, and owner (self/spouse/joint). Use for questions like 'What did Nancy Pelosi trade recently?', 'Which members bought NVDA?', or 'Show the largest Senate trades this quarter'. Filter by chamber, ticker, or member name; sort by traded value, trade count, or recency. For one member's profile and complete trading history, use get_congress_member instead.

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• compareA

  trimtab-aisA

  Put two subjects on the same axis over the same months and compute the difference: two origin countries, two commodity chapters (or HS6 codes), or two US gateways, measured on trade weight, value, unit value, tariff burden or duty paid. Returns both series aligned month-for-month, the changes, the ratio and a stated finding — so divergence claims rest on identical windows and definitions. Use for "is trade shifting from China to Vietnam", "do Indian goods pay more than Mexican goods", "is Houston growing faster than Savannah". For two ORIGINS on a specific commodity it ALSO returns `landed_cost` — the duty-inclusive $/kg for each origin AND the FOB price premium the lower-duty origin can carry at the factory and still match landed customs cost. That headroom % is the exact number to put in front of a buyer ("we can be N% pricier than China and you pay the same landed"); it also reports which origin actually lands cheaper today, so the duty gap is never oversold. Both subjects must be the same kind; to compare more than two, call twice. burden_pct/duty_usd come from nationwide receipts and are not available for kind "gateway". No API key required.

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• compareA

  us-tariff-ledgerA

  Put two subjects on the same axis over the same months and compute the difference: two origin countries, two commodity chapters (or HS6 codes), or two US gateways, measured on trade weight, value, unit value, tariff burden or duty paid. Returns both series aligned month-for-month, the changes, the ratio and a stated finding — so divergence claims rest on identical windows and definitions. Use for "is trade shifting from China to Vietnam", "do Indian goods pay more than Mexican goods", "is Houston growing faster than Savannah". For two ORIGINS on a specific commodity it ALSO returns `landed_cost` — the duty-inclusive $/kg for each origin AND the FOB price premium the lower-duty origin can carry at the factory and still match landed customs cost. That headroom % is the exact number to put in front of a buyer ("we can be N% pricier than China and you pay the same landed"); it also reports which origin actually lands cheaper today, so the duty gap is never oversold. Both subjects must be the same kind; to compare more than two, call twice. burden_pct/duty_usd come from nationwide receipts and are not available for kind "gateway". No API key required.

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• calculate_rvpiA

  tvm-fundA

  Calculate Residual Value to Paid-In capital (RVPI): the current (unrealised) value of remaining assets divided by paid-in capital. Formula: RVPI = Residual Value / Paid-In Capital. WHEN TO USE: Use for fund reporting to show the unrealised multiple still held in the portfolio (mark-to-market or fair value of remaining investments). WHEN NOT TO USE: Do NOT use alone as a performance measure — residual value is an estimate, not cash (combine with DPI for the full TVPI picture). BEHAVIOUR: pure deterministic calculation — no side effects, no network or storage access; idempotent and non-destructive; identical inputs always produce identical outputs. Division by zero, non-finite inputs, or mathematically undefined combinations return an explicit error instead of a number. RETURNS: JSON object { rvpi: number (e.g. 1.2 = 1.2x of paid-in still held), inputs }. PARAMETERS: residual_value (required): Current fair value of remaining (unrealised) investments, e.g. 1200000. Must be >= 0. paid_in (required): Paid-in capital contributed by investors, e.g. 1000000. Must be > 0.

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• cluster_tradesA

  Coldpine: Congressional Stock DisclosuresA

  Stocks that several members of Congress traded in the same direction inside a rolling window (Coldpine's cluster detection, same definition as the bot). Returns ticker, direction, distinct member count, trade count, date span, summed disclosed amount range and the member names. Same data as coldpine.io/research/biggest-cluster-buys-in-congress. Use it for 'what are several members buying (or selling) at once'; for everyone who ever traded one given stock use get_stock instead. The window counts back from the most recent trade date on record, not from a date you choose, and clusters come back largest first by distinct members. A person is counted once per cluster however many trades they made. Overlap in timing is a description of the filings, not evidence of coordination. Access: needs the agent token from a free Coldpine account, sent as 'Authorization: Bearer <token>'; without it the call returns setup steps instead of data. Read-only, cached for up to an hour.

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• mcp_crm_segments_filter_optionsA

  MailzzyA

  Get the vocabulary for building an audience segment filter. Call this BEFORE mcp_crm_segments_create or mcp_crm_segments_update so you use real field names, operators, and option ids instead of guessing. Returns: fields (each with its category, valid count operators, date operators, date units, value options, and sub-filters); lists (the tenant's groups/tags, each with a ready-to-use membership value in "typeId:id" form); and campaigns (id + name) for event filters. Use a field's 'field' string as SegmentCondition.field, an operator's 'name' as countCondition.name/dateCondition.name, a list's 'value' for a 'Member of a list' condition, and a campaign's id (as a string) in an 'Email Name' sub-filter. Tenant is bound to the session and cannot be changed via tool arguments.

  ConnectorOAuth

• compute_gst_vatA

  AI2Fin (2Fin) Tax MCPA

  Add or remove a country's GST/VAT — or its other national consumption tax, such as Japan's consumption tax or Malaysia's SST — on a monetary amount, returning the net / tax / gross split. Use it to convert between tax-exclusive and tax-inclusive prices (invoices, quotes, receipts); for the rates themselves use tax_rate_lookup. Pure arithmetic on the current standard rate, rounded to 2 decimals, in the local currency. Pass region for a state or provincial rate (CA, US): in Canada that is GST plus the provincial tax, in the US the state sales tax. A country with no national rate (the US without a region, or a country with no consumption tax) returns an explanatory error instead of a wrong number. Results may include one sourced background fact (relatedFact); the figures do not depend on it.

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• update-document-metadata-valuesA

  fynk MCPA

  Set or unset the value of one or more of a document's metadata. Use this tool when: - You want to fill in (or change) a document's metadata values - You want to remove a value the document currently has for a metadata Each entry in `metadata_value_changes` identifies the metadata by its `metadata_uuid` or `name` (use list-account-metadata, or get-document-info with include=["metadata_values"], to discover them) — sending an identifier that does not match any of the account's metadata will fail validation. Each entry also has an `operation`: - `set`: create the metadata value (if the document does not have one yet) or update the existing value - `unset`: remove the document's value for the metadata (no value is required) For a `set`, take note of the metadata's `value_type` when constructing the value. These are the rules to use when constructing the `value` string: - number: the numeric value in a string, using '.' as the decimal separator -> "1234.56" - currency: concatenate the ISO currency code and the numeric value with a ';' -> "EUR;1000.10" (for one thousand Euro and ten cents) - currency_duration: same as currency, but append another ';' followed by either `monthly` or `yearly` -> "EUR;1000.10;monthly" / "USD;1000.10;yearly" - select: one of the options from the metadata's `select_values` list -> "red" - multi_select: an array of the selected values in the `values` field -> ["red", "blue"] - bool: either of the strings "true" (displayed to the user as "Yes") or "false" (displayed to the user as "No") -> "true" / "false" - duration: a PHP-compatible duration specification -> "P6D" (6 days), "P2W" (2 weeks), "PT12H" (12 hours) - date: the date in the format "YYYY-MM-DD" -> "2026-12-31" - email, text, textarea, or any type not listed above: a string -> "test@example.com" Some metadata cannot be changed this way (e.g. computed metadata, or metadata whose value is driven by a dynamic field) — attempting to do so will fail validation.

  Connector

  Destructive

  OAuth

• update-document-metadata-valuesA

  fynk MCPA

  Set or unset the value of one or more of a document's metadata. Use this tool when: - You want to fill in (or change) a document's metadata values - You want to remove a value the document currently has for a metadata Each entry in `metadata_value_changes` identifies the metadata by its `metadata_uuid` or `name` (use list-account-metadata, or get-document-info with include=["metadata_values"], to discover them) — sending an identifier that does not match any of the account's metadata will fail validation. Each entry also has an `operation`: - `set`: create the metadata value (if the document does not have one yet) or update the existing value - `unset`: remove the document's value for the metadata (no value is required) For a `set`, take note of the metadata's `value_type` when constructing the value. These are the rules to use when constructing the `value` string: - number: the numeric value in a string, using '.' as the decimal separator -> "1234.56" - currency: concatenate the ISO currency code and the numeric value with a ';' -> "EUR;1000.10" (for one thousand Euro and ten cents) - currency_duration: same as currency, but append another ';' followed by either `monthly` or `yearly` -> "EUR;1000.10;monthly" / "USD;1000.10;yearly" - select: one of the options from the metadata's `select_values` list -> "red" - multi_select: an array of the selected values in the `values` field -> ["red", "blue"] - bool: either of the strings "true" (displayed to the user as "Yes") or "false" (displayed to the user as "No") -> "true" / "false" - duration: a PHP-compatible duration specification -> "P6D" (6 days), "P2W" (2 weeks), "PT12H" (12 hours) - date: the date in the format "YYYY-MM-DD" -> "2026-12-31" - email, text, textarea, or any type not listed above: a string -> "test@example.com" Some metadata cannot be changed this way (e.g. computed metadata, or metadata whose value is driven by a dynamic field) — attempting to do so will fail validation.

  Connector

  Destructive

  OAuth

• add_vercel_verificationA

  PNTRB

  Publish the Vercel ownership TXT value for one of your subdomains. Use it when Vercel says the domain is linked to another account and asks for a TXT at _vercel.pntr.dev: only PNTR can write that name, so do not add the value with add_dns_record. The subdomain must already point at Vercel (the CNAME or A record Vercel shows for it), and the value must name that subdomain exactly, as vc-domain-verify=<name>.pntr.dev,<code>. One value per subdomain: a new value replaces the previous one. It is removed automatically after 7 days, or as soon as the subdomain is deleted or disabled. Requires an account signed in with GitHub.

  Connector

  Destructive

  API key

• get_insider_tradesA

  DalalOS: Indian Stock Market Research (NSE/BSE)A

  Use this when the user asks which promoters, directors or company insiders bought, sold or pledged shares of Indian listed companies, market-wide or for one company. Not for bulk or block deals by funds; use get_bulk_block_deals. Get disclosed insider trades (SEBI PIT) in Indian listed companies: buys, sells and pledges by promoters, directors, KMP and designated persons, market-wide or for one stock. Omit `symbol` for the whole market, or pass an NSE symbol, ISIN or BSE code. The window is the TRADE date: `days` back from today (1..365, default 30), or `from_date`/`to_date` (ISO dates). `category`: promoters (default; promoter, promoter group, promoter-and-director) | directors_kmp | designated | relatives | all. `side`: trades (default, buys and sells) | buy | sell | pledge | all. `min_value_inr` drops smaller trades. Equity only unless `include_derivatives`. `group_by`: trade (default, newest first) | company (per-company buy, sell and net value in rupees, largest first). `limit` (1..500, default 100). Sources, both from BSE: System-Driven Disclosures (depository-generated, the complete record for these people, published 7-14 days after the trade) and company Form C (next day, adds `mode` such as market or off_market, and the holding before). A trade in both is counted once. Every response carries a `coverage_note`; the latest two weeks fill in as reports arrive. Disclosed facts only, no view on why anyone traded.

  ConnectorOAuth

• get_shipping_quoteA

  ShipSmarter ShippingA

  Get live shipping prices for one parcel from several carriers (Canada Post, UPS, FedEx and others). No account needed. Give the origin and destination postal or ZIP codes and the weight in kilograms (convert pounds and inches first); the box size is optional and a 30 x 20 x 10 cm box is assumed when it is missing. Returns up to 6 of the cheapest services with price and estimated transit time, and a link that opens the same quote on the website, where the label can be bought. Prices are the public rates at the moment of the quote. If the user is signed in, compare_shipping_rates returns their own account prices instead.

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