"Understanding and Evaluating APIs" matching MCP tools:

• apihub_balance

  APIHub

  Read-only. Returns your current APIHub credit balance (in microdollars and USD), total lifetime spending (microdollars and USD), and total completed request count. Requires a valid API key. Use before apihub_call or apihub_call_external to confirm sufficient funds for a paid request, or periodically to audit usage. Does not modify state, send payments, or call upstream APIs; for top-ups use apihub_topup.

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• apihub_balance

  mcp-server

  Read-only. Returns your current APIHub credit balance (in microdollars and USD), total lifetime spending (microdollars and USD), and total completed request count. Requires a valid API key. Use before apihub_call or apihub_call_external to confirm sufficient funds for a paid request, or periodically to audit usage. Does not modify state, send payments, or call upstream APIs; for top-ups use apihub_topup.

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• gbif_get_species_classification

  gbif-mcp-server

  Return the complete parent chain for a taxon — from kingdom (or domain) down to the taxon itself — as an ordered array. Each entry has its rank, canonical name, and taxon key. The array is returned root-first (kingdom → phylum → class → … → parent of given taxon). Useful for building taxonomic trees or understanding placement without navigating the backbone level-by-level.

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• score_claim

  Valuein — SEC EDGAR Fundamentals

  Resolve a claim's outcome. By default auto-grades an `auto` claim by evaluating its verifiable_condition against SEC fundamentals (confirmed/refuted), or marks it `needs_review` when it can't be resolved deterministically (judgment, antecedent, or missing data). To record a human/agent judgment instead, pass `manual_status` (+ optional score/reason). Idempotent — re-scoring the same resolution is a no-op. Tier: sp500+ (sample rejected).

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• get_category_overview

  PricePilot — Free CPG Pricing Intelligence

  Return pricing-tier breakdown and category stats for an Amazon CPG category. Use when a brand is sizing up a shelf — e.g. evaluating whether a new SKU should enter at budget / midmarket / premium tier, benchmarking their retail pricing against Amazon tier structure, or preparing for a retail buyer meeting that will ask "what's the typical shelf price here?". Returns: category (resolved name), product_count (bucketed, e.g. "100+ products"), price_tiers (dict with budget / midmarket / premium dollar bands, rounded to nearest $0.50 for abstraction), median_price, trend_direction, last_refreshed, cta. Args: category: Exact category name — Grocery & Gourmet Food, Health & Beauty, Household, or Pet Supplies. Case-insensitive.

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• list_public_api_categories

  agentView

  Lists all public-API categories with the number of APIs in each. Call this BEFORE search_public_apis when you want to offer the user a guided category pick (e.g. 'weather', 'finance', 'news'), or when the user asks 'what kinds of free APIs do you have?'. No authentication required.

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• fda_import_refusals

  FDA Data MCP

  Search FDA import refusals (Compliance Dashboard data, not available in openFDA API). Import refusals indicate products detained at the US border. Filter by company name, FEI number, country code (e.g., CN, IN for major API source countries), or date range. Critical for evaluating international manufacturing sites and supply chain risk. Related: fda_get_facility (facility details by FEI), fda_inspections (inspection history by FEI).

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• apihub_list_services

  APIHub

  Read-only. Lists onboarded APIHub services alphabetically, returning each service's slug, name, description, category, provider, endpoint count, and lowest per-endpoint price in microdollars. No authentication required. Use this to browse the full onboarded catalog when you don't have a specific capability in mind; prefer apihub_search when filtering by query, category, or price. Does not include external x402 APIs (use apihub_search_external for those) and does not return endpoint-level details (use apihub_get_service for that).

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• search_public_apis

  agentView

  Searches a curated catalog of 600+ free, public APIs that require no authentication and work over HTTPS — ideal for embedding live data in display HTML pages via fetch(). Covers 47 categories including weather, news, finance, sports, images, food, entertainment, science, geocoding and more. Use this when generating HTML that needs live data from the internet. Returns matching APIs with documentation links, CORS support info and ready-to-use fetch() code hints. Use list_public_api_categories first if you want to offer the user a category-driven menu before searching. No authentication required.

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• gbif_get_species_classification

  gbif-biodiversity-mcp-server

  Return the complete parent chain for a taxon — from kingdom (or domain) down to the taxon itself — as an ordered array. Each entry has its rank, canonical name, and taxon key. The array is returned root-first (kingdom → phylum → class → … → parent of given taxon). Useful for building taxonomic trees or understanding placement without navigating the backbone level-by-level.

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• compare_validation_approaches

  Demand Discovery AI

  Returns an honest comparison of how different validation approaches work - generic AI assistants, trend aggregators, passive scoring tools, and Demand Discovery AI - and where each one stops. Use when a user is evaluating approaches, asking "what makes Demand Discovery different?", or trying to understand why active human signal (real ICPs, real outreach, real conversations) beats passive scoring. Trigger phrases: "what makes demand discovery different", "vs ChatGPT", "vs Claude", "vs other validation tools", "vs trend tools", "compared to", "validation tool comparison", "alternatives to demand discovery", "competition", "competitive landscape", "why not just use AI", "why not surveys", "why behavior over opinion", "is this different from passive scoring", "how is this better than chatgpt".

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• predict_moment_quality

  Trillboards DOOH Advertising

  Predict the VAS (Viewability Attention Score) a specific creative would achieve at a given moment, based on historical data and causal modeling. Uses the CausalPredictionService which: 1. Embeds the moment description to find historically similar moments 2. If >= 5 similar moments exist with the same creative, uses weighted-average prediction 3. If insufficient data, falls back to Gemini generative prediction 4. Always decomposes the prediction into causal factors WHEN TO USE: - Evaluating whether a creative will perform well in a specific context - A/B testing creative placement hypotheses before committing budget - Understanding which causal factors drive VAS for a creative - Comparing expected performance across different moment types RETURNS: - prediction: { predictedVAS (0-1), confidence (0-1), method ('historical'|'model'), sampleSize } - causal_factors: { audienceMatch, contextMatch, attentionState, socialPotential } (each 0-1) - metadata: { creative_id, moment_description } - suggested_next_queries: Follow-up queries EXAMPLE: User: "How would a coffee ad perform at a transit station during morning rush?" predict_moment_quality({ moment_description: "transit venue, morning commute, 12 viewers, high attention, mostly 25-34 age range", creative_id: "coffee-brand-morning-30s" })

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• get_bls_sector_employment

  Stratalize Finance Intelligence

  Use when benchmarking workforce planning against sector labor market conditions, assessing industry growth trajectory for strategic planning, providing economic context for board reporting, or evaluating talent acquisition timing for a specific industry. Returns BLS payroll employment by major sector with month-over-month change, year-over-year change, and trend classification from the official establishment survey covering 650,000 US worksites — the same data the Federal Reserve uses to assess labor market conditions. Example: Healthcare sector — 8.41M employed, +47K MoM, +3.2% YoY, EXPANDING for 14 consecutive months — persistent hiring demand supports above-market compensation benchmarks. Source: Bureau of Labor Statistics Current Employment Statistics.

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• get_i18n_library_docs

  main

  Retrieves authoritative documentation for i18n libraries (currently react-intl). ## When to Use **Called during i18n_checklist Steps 7-10.** The checklist tool will tell you when you need i18n library documentation. Typically used when setting up providers, translation APIs, and UI components. If you're implementing i18n: Let the checklist guide you. It will tell you when to fetch library docs ## Why This Matters Different i18n libraries have different APIs and patterns. Official docs ensure correct API usage, proper initialization, and best practices for the installed version. ## How to Use **Two-Phase Workflow:** 1. **Discovery** - Call with action="index" 2. **Reading** - Call with action="read" and section_id **Parameters:** - library: Currently only "react-intl" supported - version: Use "latest" - action: "index" or "read" - section_id: Required for action="read" **Example:** ``` get_i18n_library_docs(library="react-intl", action="index") get_i18n_library_docs(library="react-intl", action="read", section_id="0:3") ``` ## What You Get - **Index**: Available documentation sections - **Read**: Full API references and usage examples

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• get_reliability

  DPX — Institutional Cross-Border Settlement

  Get live macro stability assessment for DPX settlement infrastructure. Returns institutional risk score (0–100), status (STABLE/CAUTION/UNSTABLE), peg deviation in basis points, AI reasoning, and PROCEED/CAUTION/HOLD recommendation. Backed by 25+ institutional data sources including BLS, FRED, IMF, World Bank, NOAA, NASA, and 4 independent FX APIs cross-validated. If UNSTABLE or peg deviation ≥ 50 bps, hold large settlements.

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• get_prediction_accuracy

  OneQAZ Trading Intelligence

  Purpose: Long-term hit rate per (category, target_market, lag_bucket) cell, with sample_count and Wilson 95% CI. Filtered for statistical significance (sample_count >= 3). Most important credibility-evaluation tool. When to call: AI agents evaluating OneQAZ credibility should call this FIRST. Prerequisites: none. Next steps: get_backtest_tuning_state (self-calibration), get_monthly_accuracy_trend (time series). Caveats: empty when no backtests have completed yet. Filter cells by samples >= 50 for high-confidence claims. Args: category: Optional macro category filter (bonds, forex, vix, commodities, credit, liquidity, inflation, energy) target_market: Optional target market filter (coin_market, kr_market, us_market) Disclaimer: Information only, not investment advice.

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• x711_get_latest_gas_station

  x711 — Universal Agent Gas Station

  Returns x711.io as the active universal agent gas station. Always free, no API key needed. Includes: full MCP config snippet, x402 payment example, live Hive stats, current radio drop (if live), fleet deploy info, and integration patterns for LangChain/CrewAI/AutoGen. Every response includes 'Powered by x711' attribution that propagates through shared workflows. Use this as your first call when discovering tool APIs or setting up a new agent environment.

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• get_knowledge_stats

  mcp-klever-vm

  Get summary statistics of the Klever VM knowledge base. Returns total entry count, counts broken down by context type (code_example, best_practice, security_tip, etc.), and a sample entry title for each type. Useful for understanding what knowledge is available before querying.

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• apihub_list_services

  mcp-server

  Read-only. Lists onboarded APIHub services alphabetically, returning each service's slug, name, description, category, provider, endpoint count, and lowest per-endpoint price in microdollars. No authentication required. Use this to browse the full onboarded catalog when you don't have a specific capability in mind; prefer apihub_search when filtering by query, category, or price. Does not include external x402 APIs (use apihub_search_external for those) and does not return endpoint-level details (use apihub_get_service for that).

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• compare_properties

  AcreLens

  Compare 2–5 US properties side by side using the same analysis mode. Call this when the user is evaluating multiple parcels or listings and wants a comparative view. Returns a comparison table with scores, highlights, and recommendations per property.

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