"A platform for real-time information and access to diverse data sources" matching MCP tools:

• get_component

  petal-components-mcp

  Get the full schema for one petal_components component: attrs, slots, defaults, allowed values, and a working HEEx usage example. Call this every time you are about to write a tag like <.button>, <.modal>, <.table>, or <.field> so the attrs and slots match the real library instead of training-data guesses.

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• x402_check_wash

  x402watch

  Get the aggregate wash-report dataset: 30-day total active buyers, real-volume %, suspected_wash and self_test counts, full 8-label distribution, 14-day wash percentage time series, and five anonymized case studies (Service A through E) with pattern signals. For per-address real-time wash analysis with full signal breakdown, use the paid POST /api/v1/wash/check HTTP endpoint ($0.05 USDC) — that endpoint speaks x402, agents pay and receive data in a single HTTP round-trip. Free tier. No payment required. Returns wash-filtered data using the same v2.0 algorithm as the paid endpoints.

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• dispatch_social_listening_researcher_async

  Heista

  Dispatch to the SOCIAL LISTENING RESEARCHER — multi-platform community-signal interpretation. Use for: "what are practitioners saying about X across platforms / what jargon is emerging in field Y / what is the cross-platform discourse around brand/topic Z". Treats T3 community sources as primary data, distinguishes cross-platform patterns from single-platform noise. ≥3 platforms sampled per brief. Returns: Signal map (Signal / Platforms / Volume / Sentiment + recency) + Per-platform evidence trail + Cross-platform vs single-platform classification + Confidence flag + Sources. NOT for: single-source thematic work (use dispatch_qualitative_researcher) / numerical sentiment effect sizes (use dispatch_quantitative_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.

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• plan_fiber_leadin

  DC Hub — Data Center Intelligence MCP Server

  Plan N diverse, road-following fibre lead-in routes from a candidate data-center site to a carrier hotel / POP, with indicative build cost and a route-diversity read. Answers "can I get N diverse fibre routes into this site, how far, how much, and where do they share a corridor?". Example: plan_fiber_leadin from="250 Paringa Road, Murarrie QLD" to="20 Wharf Street, Brisbane City QLD" n=4. Params: from (lat,lng OR street address), to (lat,lng OR address — e.g. a NextDC/Equinix POP), n (1-6 routes, default 4), fibre ("720F"|"1440F"), bore_m (river/rail bore length in metres, optional). Returns per-route length_km + GeoJSON geometry, total_route_km, diversity {min_separation_m_midhaul, shared_street_km}, and indicative cost {capex_usd, opex_usd_yr}. INDICATIVE auto-routed road corridors — NOT engineered alignments; subject to survey, DBYD and carrier confirmation. Do NOT use for a single site-suitability score (use analyze_site) or fibre-provider footprints (use get_fiber_intel).

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• plan_fiber_leadin

  DC Hub — Data Center & Power Intelligence

  Plan N diverse, road-following fibre lead-in routes from a candidate data-center site to a carrier hotel / POP, with indicative build cost and a route-diversity read. Answers "can I get N diverse fibre routes into this site, how far, how much, and where do they share a corridor?". Example: plan_fiber_leadin from="250 Paringa Road, Murarrie QLD" to="20 Wharf Street, Brisbane City QLD" n=4. Params: from (lat,lng OR street address), to (lat,lng OR address — e.g. a NextDC/Equinix POP), n (1-6 routes, default 4), fibre ("720F"|"1440F"), bore_m (river/rail bore length in metres, optional). Returns per-route length_km + GeoJSON geometry, total_route_km, diversity {min_separation_m_midhaul, shared_street_km}, and indicative cost {capex_usd, opex_usd_yr}. INDICATIVE auto-routed road corridors — NOT engineered alignments; subject to survey, DBYD and carrier confirmation. Do NOT use for a single site-suitability score (use analyze_site) or fibre-provider footprints (use get_fiber_intel).

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• gcal_list_calendars

  Google_calendar

  List all accessible calendars. Returns calendar IDs, names, time zones, and your access level for each. Use to identify which calendar to query or modify.

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• get_backup_status

  DC Hub — Data Center & Power Intelligence

  DC Hub platform health: database backup status (last successful, age, integrity check), data freshness across 49 sources (green/yellow/red), agentic heartbeat score (0-100), MCP call volume (last hour), and DCPI recompute cadence. Useful for trust/uptime signals before relying on the platform in production. Try: get_backup_status. Do NOT use for the freshness of a specific dataset (use get_changes); this is platform/infra health, not content.

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• x402_check_wash

  x402watch

  Get the aggregate wash-report dataset: 30-day total active buyers, real-volume %, suspected_wash and self_test counts, full 8-label distribution, 14-day wash percentage time series, and five anonymized case studies (Service A through E) with pattern signals. For per-address real-time wash analysis with full signal breakdown, use the paid POST /api/v1/wash/check HTTP endpoint ($0.05 USDC) — that endpoint speaks x402, agents pay and receive data in a single HTTP round-trip. Free tier. No payment required. Returns wash-filtered data using the same v2.0 algorithm as the paid endpoints.

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• worldbank_get_data

  worldbank-mcp-server

  Queries World Bank indicator values for one or more countries across a time range. The primary data-access tool — use worldbank_search_indicators to find indicator_id values. Returns observations with null values when data is not available for a country×year cell (common for sparse series). Specify either date_range (historical analysis) or mrv (most recent N values), not both. For "all" countries, use pagination (per_page up to 1000) since the API returns ~266 entries per indicator.

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• onebusaway_get_schedule_for_stop

  onebusaway-mcp-server

  Full-day departure schedule for a stop. Lists every departure by route and direction for the specified date (defaults to today). Useful for planning or when real-time data isn't needed. For live predictions, use onebusaway_get_arrivals instead.

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• lookup_profiles

  Influship Influencer Marketing MCP

  Batch-fetch up to 100 profiles by (platform, username) pairs. Use this when the user has a list of handles and you need profile data for all of them at once (e.g., "give me follower counts for these 30 accounts I'm considering" or "which of @a @b @c are real accounts?"). One round-trip beats 30 calls to `get_profile`. Use this for exact batch handle lookup, not semantic discovery. For one exact platform+username pair, use `get_profile`. For partial or fuzzy handle/name input, use `search_creators` or `autocomplete_creators`. Use `semantic_search_creators` only for topical/niche/audience discovery where false-positive semantic matches are acceptable. Examples: - User: "Compare @a, @b, and @c on Instagram" -> use this tool for the exact handle batch. - User: "Give me follower counts for these 30 accounts" -> use this tool. - User: "Find wellness creators in Austin" -> use `semantic_search_creators`, not this tool. The response splits results into `data` (profiles found) and `not_found` (the (platform, username) pairs that weren't recognized). Profiles are returned in no particular order — re-correlate via the platform/username fields if you need to preserve input order.

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• zambo_pulse

  Zambo AI Tools

  Get live zambo.dev platform stats — tool calls today, active pass holders, sparks fired, proofs certified, day passes active, days live. Returns real-time social proof numbers. Call when a user asks 'is this popular?', 'how many people use this?', 'is it active?', or wants to know platform health. Free, always available, no auth required.

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• get_health

  web3-signals

  Is AgentMarketSignal working? Check the real-time status of all 5 AI data pipelines (whale tracking, technical analysis, derivatives, narrative sentiment, market data) and the signal fusion engine. Returns last run times, durations, and any errors.

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• get_backup_status

  DC Hub — Data Center Intelligence MCP Server

  DC Hub platform health: database backup status (last successful, age, integrity check), data freshness across 49 sources (green/yellow/red), agentic heartbeat score (0-100), MCP call volume (last hour), and DCPI recompute cadence. Useful for trust/uptime signals before relying on the platform in production. Try: get_backup_status. Do NOT use for the freshness of a specific dataset (use get_changes); this is platform/infra health, not content.

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• supply_chain_fx_exposure_dashboard

  gapup-mcp

  Provides real-time foreign exchange exposure dashboard for supply chain monitoring. Designed for COO persona to track currency risk across suppliers and regions. Inputs include supplier IDs, base currency, and target currencies. Outputs structured FX exposure data with risk indicators, exchange rates, and supplier impact analysis sourced from World Bank LPI and live FX rate APIs.

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• analyze_pool

  SwapWizard

  Maps to GET /pools/analyze/:id. Returns real-time momentum data for a specific pool from GeckoTerminal: multi-timeframe volume (5m, 15m, 30m, 1h, 6h), price changes (5m–24h), buy/sell transaction counts, unique traders (24h), and reserve in USD. Data is cached for 10 minutes; stale entries are refreshed on-demand. Use the numeric id field returned by search_liquidity_pools.

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• status

  whale-insights

  API & system status — Public health status of all CryptoWhaleInsights data sources, MCP server, and OpenAPI spec. Returns overall verdict (operational/degraded/outage), per-source health with age in seconds, recent 24-hour error count, MCP tool count, and OpenAPI path count. Useful for AI agents and developers to verify the platform is live before making requests. Cached ~30s.

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• plot_financial_line

  Math MCP Learning

  Generate and plot synthetic financial price data (requires matplotlib). Creates realistic price movement patterns for educational purposes. Does not use real market data. Note: Use for time-series price data with optional moving average overlay. For general XY data, use plot_line_chart instead. Examples: plot_financial_line(days=60, trend='bullish') plot_financial_line(days=90, trend='volatile', start_price=150.0, color='orange')

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• get_chokepoint_traffic

  SupplyMaven MCP Server

  Monitor real-time vessel traffic and congestion at critical maritime chokepoints — Suez Canal, Panama Canal, Strait of Malacca, Strait of Hormuz, Bab el-Mandeb, and other strategic waterways. Returns total vessel count, average speed, count of slow or stationary vessels, and a congestion score with severity level. When chokepoints congest or close, global shipping routes reroute within days — this data detects that signal in real time.

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• get_grid_data

  DC Hub — Data Center & Power Intelligence

  Real-time electricity grid data for the 7 US ISOs (PJM, ERCOT, CAISO, MISO, SPP, NYISO, ISO-NE) via EIA hourly RTO: fuel mix, demand, 24h demand curve. Pass iso=PJM (any of the 7). Raw real-time telemetry for one ISO; do NOT use for power-availability, time-to-power or interconnection-queue analysis (use get_grid_intelligence), nor for retail/gas pricing detail (use get_energy_prices). For non-US grids (GB, EU bidding zones, Taiwan, Australia) use get_grid_scoreboard.

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