"Vehicle Trade-In Value Calculator for Canada" matching MCP tools:

• mg_calculator_profit_margin_update

  Marketgenius

  Update one or more fields in the already-open Profit Margin Calculator. ALWAYS call mg_calculator_profit_margin_state first — the user may have changed values manually in the GUI and you must not overwrite them. Pass the version you received from that call (or from the open tool if updating immediately after opening). Only pass the fields the user explicitly asked to change; omit all others. Send all changes in a single call — multiple sequential calls lose intermediate updates (only the last one applies).

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• mg_calculator_market_cap_update

  Marketgenius

  Update one or more fields in the already-open Market Cap Calculator. ALWAYS call mg_calculator_market_cap_state first — the user may have changed values manually in the GUI and you must not overwrite them. Pass the version you received from that call (or from the open tool if updating immediately after opening). Only pass the fields the user explicitly asked to change; omit all others. Send all changes in a single call — multiple sequential calls lose intermediate updates (only the last one applies).

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• mg_calculator_profit_margin_update

  Marketgenius

  Update one or more fields in the already-open Profit Margin Calculator. ALWAYS call mg_calculator_profit_margin_state first — the user may have changed values manually in the GUI and you must not overwrite them. Pass the version you received from that call (or from the open tool if updating immediately after opening). Only pass the fields the user explicitly asked to change; omit all others. Send all changes in a single call — multiple sequential calls lose intermediate updates (only the last one applies).

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• smart_traders_and_funds_perp_trades

  Nansen

  Get recent Hyperliquid perpetual futures trades from Smart Traders and Funds across all tokens. This tool provides granular smart trader and funds activity. For a big picture view of smart traders and funds activity across all tokens, use token_discovery_screener with traderType="sm" filter. **Note:** This endpoint is Hyperliquid-only (perpetual futures data). It returns recent trades only (no date filtering available). Columns returned: - **Time**: Timestamp when the trade occurred (datetime: YYYY-MM-DD HH:MM:SS) - **Side**: Position direction - Long or Short - **Action**: Order action - Add, Reduce, Open, Close - **Token**: Symbol of the perpetual contract - **Size**: Quantity of the perpetual contract (numeric) - **Price USD**: Price per token at time of trade (price formatted) - **Value USD**: Total USD value of the trade (currency formatted) - **Trader**: Nansen label of the trading address - **Tx Hash**: Blockchain transaction hash for verification Sorting Options (all fields support "asc"/"desc"): Available for sorting: timestamp, valueUsd, amount, priceUsd Examples: # Get recent smart money perp trades (sorted by value) ``` { "order_by": "valueUsd", "order_by_direction": "desc" } ``` # Filter by action and side ``` { "action": "Open", "side": "Long", "includeSmartMoneyLabels": ["Fund", "All Time Smart Trader"] } ```

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• mg_calculator_market_cap_sync

  Marketgenius

  Sync user-entered field values of the open Market Cap Calculator back to the session store so the model can read them via the state tool. Called by the View after any field change; hidden from the model.

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• token_dex_trades

  Nansen

  Get DEX trades for a specific token. **Modes:** - `onchain_tokens` (default): Analyze on-chain tokens by contract address - `perps`: Analyze Hyperliquid perpetual futures by symbol (chain auto-set to "hyperliquid") **NOTE:** In onchain_tokens mode, only ETH is supported among native tokens. For other native tokens (SOL, BTC, BNB, etc.), use perps mode instead. Args: request: TokenDexTradesRequest containing parameters, pagination settings, and optional sorting Returns: DEX trading activity as markdown. Returns empty string if no trades found. **Common Columns (all modes):** - **Time**: Timestamp when the trade occurred (datetime: YYYY-MM-DD HH:MM:SS) - **Token**: Symbol of the token/perpetual contract - **Price USD**: Price per token in USD at time of trade (currency formatted) - **Value USD**: Total USD value of the trade/position change (currency formatted) - **Trader**: Nansen label or name of the trading address - **Tx Hash**: Blockchain transaction hash for verification **onchain_tokens mode:** - **Action**: Trade direction - BUY or SELL from perspective of the token - **Token Amount**: Quantity of the target token traded (numeric) - **Traded Amount**: Quantity of the other token in the swap (numeric) - **Traded Token**: Symbol of the token traded against (e.g., WETH, USDC) **perps mode:** - **Side**: Position direction - Long or Short - **Action**: Order action - Add, Reduce, Open, Close - **Size**: Quantity of the perpetual contract (numeric) Sorting Options (all fields support "asc"/"desc"): Available for sorting: timestamp, valueUsd, amount, priceUsd Examples: # On-chain tokens (default mode) ``` { "mode": "onchain_tokens", "chain": "ethereum", "tokenAddress": "0xa0b86a33e6b6c4b3add000b44b3a1234567890ab", "dateRange": {"from": "24H_AGO", "to": "NOW"} } ``` # Hyperliquid perpetual futures ``` { "mode": "perps", "tokenAddress": "PENGU", "dateRange": {"from": "7D_AGO", "to": "NOW"}, "action": "Open", "side": "Long" } ``` # Find biggest trades by USD value (whale watching) ``` { "mode": "onchain_tokens", "chain": "ethereum", "tokenAddress": "0xa0b86a33e6b6c4b3add000b44b3a1234567890ab", "dateRange": {"from": "7D_AGO", "to": "NOW"}, "order_by": "valueUsd", "order_by_direction": "desc" } ``` # Find who bought the dip vs who bought the top (price analysis) ``` { "chain": "ethereum", "tokenAddress": "0xa0b86a33e6b6c4b3add000b44b3a1234567890ab", "dateRange": {"from": "30D_AGO", "to": "NOW"}, "order_by": "priceUsd", "order_by_direction": "asc" } ```

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• mg_calculator_profit_margin_sync

  Marketgenius

  Sync user-entered field values of the open Profit Margin Calculator back to the session store so the model can read them via the state tool. Called by the View after any field change; hidden from the model.

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• mg_calculator_cagr_update

  Marketgenius

  Update one or more fields in the already-open CAGR Calculator. ALWAYS call mg_calculator_cagr_state first — the user may have changed values manually in the GUI and you must not overwrite them. Pass the version you received from that call (or from the open tool if updating immediately after opening). Only pass the fields the user explicitly asked to change; omit all others. Send all changes in a single call — multiple sequential calls lose intermediate updates (only the last one applies).

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• mg_calculator_profit_margin_sync

  Marketgenius

  Sync user-entered field values of the open Profit Margin Calculator back to the session store so the model can read them via the state tool. Called by the View after any field change; hidden from the model.

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• export_dataset

  Trillboards DOOH Advertising

  Export observation data as a structured dataset. Supports filtering by time, geography, venue type, and observation family. Applies k-anonymity (k=5) to protect individual privacy. Queries the relevant table based on the selected dataset type, applies filters, enforces k-anonymity by suppressing groups with fewer than 5 observations, and returns structured data. WHEN TO USE: - Exporting audience data for external analysis - Building datasets for machine learning or reporting - Getting structured vehicle or commerce data for a specific time/place - Creating cross-signal datasets for correlation analysis RETURNS: - data: Array of dataset rows (schema varies by dataset type) - metadata: { row_count, k_anonymity_applied, export_id, dataset, filters_applied, time_range } - suggested_next_queries: Related exports or analyses Dataset types: - observations: Raw observation stream data (all families) - audience: Audience-specific data (face_count, demographics, attention, emotion) - vehicle: Vehicle counting and classification data - cross_signal: Pre-computed cross-signal correlation insights EXAMPLE: User: "Export audience data from retail venues last week" export_dataset({ dataset: "audience", filters: { time_range: { start: "2026-03-09", end: "2026-03-16" }, venue_type: ["retail"] }, format: "json" }) User: "Get vehicle data near geohash 9q8yy" export_dataset({ dataset: "vehicle", filters: { time_range: { start: "2026-03-15", end: "2026-03-16" }, geo: "9q8yy" } })

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• get_route_static

  Lviv Public Transport

  Returns static route metadata: short and long name, vehicle type, brand colour, ordered stop lists for both directions, and route polylines (shapes) for map rendering. Use when the user asks which stops a route serves, what a route looks like on a map, or what the scheduled departure times are. Do NOT use this when live vehicle positions are needed — use `get_route_realtime` instead. Requires a route short name (e.g. "T30", "32A") or numeric external ID; call `get_stops_around_location` first if you only know a location and need to discover which routes serve it.

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• mg_calculator_dividend_update

  Marketgenius

  Update one or more fields in the already-open Dividend Calculator. ALWAYS call mg_calculator_dividend_state first — the user may have changed values manually in the GUI and you must not overwrite them. Pass the version you received from that call (or from the open tool if updating immediately after opening). Only pass the fields the user explicitly asked to change; omit all others. Send all changes in a single call — multiple sequential calls lose intermediate updates (only the last one applies).

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• update_bonus_entries

  Sweeppea MCP

  Update the bonus entries value for a participant in a sweepstakes. This overwrites the current value. Use get_participant first to check current bonus entries. # update_bonus_entries ## When to use Update the bonus entries value for a participant in a sweepstakes. This overwrites the current value. Use get_participant first to check current bonus entries. ## Pre-calls required 1. fetch_sweepstakes if the user gave you a sweepstakes name instead of a token ## Parameters to validate before calling - sweepstakes_token (string, required) — The sweepstakes token (UUID format) - participant_token (string, required) — The participant token (UUID format) - bonus_entries (integer, required) — range: 0–1000000 — New bonus entries value (0-1000000). This overwrites the current value.

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• mg_calculator_market_cap_update

  Marketgenius

  Update one or more fields in the already-open Market Cap Calculator. ALWAYS call mg_calculator_market_cap_state first — the user may have changed values manually in the GUI and you must not overwrite them. Pass the version you received from that call (or from the open tool if updating immediately after opening). Only pass the fields the user explicitly asked to change; omit all others. Send all changes in a single call — multiple sequential calls lose intermediate updates (only the last one applies).

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• mg_calculator_dividend_update

  Marketgenius

  Update one or more fields in the already-open Dividend Calculator. ALWAYS call mg_calculator_dividend_state first — the user may have changed values manually in the GUI and you must not overwrite them. Pass the version you received from that call (or from the open tool if updating immediately after opening). Only pass the fields the user explicitly asked to change; omit all others. Send all changes in a single call — multiple sequential calls lose intermediate updates (only the last one applies).

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• get_food_environment

  USDA Food Access

  Get county-level food access risk profiles using Census ACS data. Constructs food access risk profiles by combining vehicle access (B25044), poverty status (B17001), and SNAP participation (B22001). Limited vehicle access combined with high poverty indicates food desert risk. Useful for identifying areas with barriers to food access in grant applications. Args: state: Two-letter state abbreviation (e.g. 'WA', 'MS') or 2-digit FIPS code. county_fips: Three-digit county FIPS code (e.g. '033' for King County, WA). Omit to get all counties in the state.

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• add_domain_dns

  BorealHost

  Add a DNS record to a domain. Requires: API key with write scope. Args: domain_name: Full domain name (e.g. "example.com") record_type: "A", "AAAA", "CNAME", "MX", "TXT", or "SRV" value: Record value (e.g. "1.2.3.4" for A, "mail.example.com" for MX) subdomain: Subdomain part (e.g. "www", "mail"). Empty for apex domain. ttl: Time to live in seconds (default: 3600) priority: MX priority (required for MX records) Returns: {"success": true, "record": {"id": "...", "type": "A", "subdomain": "www", "value": "1.2.3.4", "ttl": 3600}} Errors: VALIDATION_ERROR: Missing value, invalid record type NOT_FOUND: Domain not found

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• token_dex_trades

  Nansen

  Get DEX trades for a specific token. **Modes:** - `onchain_tokens` (default): Analyze on-chain tokens by contract address - `perps`: Analyze Hyperliquid perpetual futures by symbol (chain auto-set to "hyperliquid") **NOTE:** In onchain_tokens mode, only ETH is supported among native tokens. For other native tokens (SOL, BTC, BNB, etc.), use perps mode instead. Args: request: TokenDexTradesRequest containing parameters, pagination settings, and optional sorting Returns: DEX trading activity as markdown. Returns empty string if no trades found. **Common Columns (all modes):** - **Time**: Timestamp when the trade occurred (datetime: YYYY-MM-DD HH:MM:SS) - **Token**: Symbol of the token/perpetual contract - **Price USD**: Price per token in USD at time of trade (currency formatted) - **Value USD**: Total USD value of the trade/position change (currency formatted) - **Trader**: Nansen label or name of the trading address - **Tx Hash**: Blockchain transaction hash for verification **onchain_tokens mode:** - **Action**: Trade direction - BUY or SELL from perspective of the token - **Token Amount**: Quantity of the target token traded (numeric) - **Traded Amount**: Quantity of the other token in the swap (numeric) - **Traded Token**: Symbol of the token traded against (e.g., WETH, USDC) **perps mode:** - **Side**: Position direction - Long or Short - **Action**: Order action - Add, Reduce, Open, Close - **Size**: Quantity of the perpetual contract (numeric) Sorting Options (all fields support "asc"/"desc"): Available for sorting: timestamp, valueUsd, amount, priceUsd Examples: # On-chain tokens (default mode) ``` { "mode": "onchain_tokens", "chain": "ethereum", "tokenAddress": "0xa0b86a33e6b6c4b3add000b44b3a1234567890ab", "dateRange": {"from": "24H_AGO", "to": "NOW"} } ``` # Hyperliquid perpetual futures ``` { "mode": "perps", "tokenAddress": "PENGU", "dateRange": {"from": "7D_AGO", "to": "NOW"}, "action": "Open", "side": "Long" } ``` # Find biggest trades by USD value (whale watching) ``` { "mode": "onchain_tokens", "chain": "ethereum", "tokenAddress": "0xa0b86a33e6b6c4b3add000b44b3a1234567890ab", "dateRange": {"from": "7D_AGO", "to": "NOW"}, "order_by": "valueUsd", "order_by_direction": "desc" } ``` # Find who bought the dip vs who bought the top (price analysis) ``` { "chain": "ethereum", "tokenAddress": "0xa0b86a33e6b6c4b3add000b44b3a1234567890ab", "dateRange": {"from": "30D_AGO", "to": "NOW"}, "order_by": "priceUsd", "order_by_direction": "asc" } ```

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• manage_dns

  BorealHost

  Create or delete DNS records for a site. Requires: API key with write scope. Args: slug: Site identifier action: "create" or "delete" record_type: "A", "AAAA", "CNAME", "MX", "TXT", or "SRV" subdomain: Subdomain part (e.g. "www", "mail"). Leave empty for the apex/root domain. value: Record value. Required for "create". Examples: A: "1.2.3.4", CNAME: "example.com", MX: "mail.example.com", TXT: "v=spf1 include:_spf.google.com ~all" ttl: Time to live in seconds (default: 3600) Returns: {"success": true, "record": {"type": "A", "subdomain": "www", "value": "1.2.3.4", "ttl": 3600}} Errors: VALIDATION_ERROR: Missing value for create, invalid record type NOT_FOUND: Unknown slug

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• anomaly_detect

  Trillboards DOOH Advertising

  Detect anomalies in observation patterns. Alert when metrics deviate significantly from trailing averages. Computes trailing mean and standard deviation for a given metric from the observation_stream, then identifies observations that fall beyond the configured sigma threshold (z-score based anomaly detection). WHEN TO USE: - Monitoring for unusual audience patterns (sudden spikes or drops in face count) - Detecting equipment anomalies (confidence drops indicating sensor issues) - Identifying unusual commerce or vehicle patterns - Finding outlier moments that may indicate events, incidents, or opportunities RETURNS: - anomalies: Array of anomalous observations with: - observation_id, device_id, venue_type, observed_at - metric_value: The observed value - z_score: How many standard deviations from the mean - direction: 'above' or 'below' the mean - payload: Full observation payload for context - baseline: { mean, stddev, sample_count, lookback_hours } - suggested_next_queries: Follow-up queries to investigate anomalies EXAMPLE: User: "Are there any unusual audience patterns at retail venues?" anomaly_detect({ metric: "face_count", venue_type: "retail", lookback_hours: 24, threshold_sigma: 2.0 }) User: "Detect anomalies in vehicle counts at this screen" anomaly_detect({ metric: "vehicle_count", screen_id: "507f1f77bcf86cd799439011", lookback_hours: 48, threshold_sigma: 2.5 })

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