"IATA" matching MCP tools:

• pipeworx_feedback

  Data Govt Nz

  Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

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• entity_profile

  Data Govt Nz

  Get everything about a company in one call. Use when a user asks "tell me about X", "give me a profile of Acme", "what do you know about Apple", "research Microsoft", "brief me on Tesla", or you'd otherwise need to call 10+ pack tools across SEC EDGAR, SEC XBRL, USPTO, news, and GLEIF. Returns recent SEC filings, latest revenue/net income/cash position fundamentals, USPTO patents matched by assignee, recent news mentions, and the LEI (legal entity identifier) — all with pipeworx:// citation URIs. Pass a ticker like "AAPL" or zero-padded CIK like "0000320193".

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• compare_entities

  Data Govt Nz

  Compare 2–5 companies (or drugs) side by side in one call. Use when a user says "compare X and Y", "X vs Y", "how do X, Y, Z stack up", "which is bigger", or wants tables/rankings of revenue / net income / cash / debt across companies — or adverse events / approvals / trials across drugs. type="company": pulls revenue, net income, cash, long-term debt from SEC EDGAR/XBRL for tickers like AAPL, MSFT, GOOGL. type="drug": pulls adverse-event report counts (FAERS), FDA approval counts, active trial counts. Returns paired data + pipeworx:// citation URIs. Replaces 8–15 sequential agent calls.

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• remember

  Data Govt Nz

  Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

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• fda_facility_dossier

  FDA Data MCP

  Compliance-first facility dossier by FEI number. Returns the facility profile plus recent inspections, citations, warning letters, import refusal history, import-alert mentions, recall context, freshness, and recommended next tools. Use this when you want the fastest FEI-level manufacturing risk view instead of the broader product-focused facility profile.

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• fda_search_510k

  FDA Data MCP

  Search FDA 510(k) clearances across all companies. Filter by company name (fuzzy match), product code, decision code (e.g., SESE=substantially equivalent), clearance type (Traditional, Special, Abbreviated), and date range. Returns clearance number (K-number), applicant, device name, decision date, and product code. Related: fda_device_class (product code details and classification), fda_product_code_lookup (cross-reference a product code across 510(k) and PMA), fda_search_pma (PMA approvals for higher-risk devices).

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• get_nonprofit_details

  IRS 990 Nonprofit Data

  Get detailed information about a nonprofit organization by EIN. Returns comprehensive data from the organization's IRS 990 filings including revenue, expenses, assets, executive compensation, and filing history. Use search_nonprofits first to find the EIN. Args: ein: Employer Identification Number (e.g. '13-1837418' or '131837418').

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• fda_get_facility

  FDA Data MCP

  Detailed facility profile by FEI number. Returns: facility name, full address, operations type (Manufacture, API, Repack, Contract Manufacture, etc.), establishment types (Manufacturer, Distributor, Specification Developer, etc.), registrant and owner/operator info, DUNS number, registration expiry, enforcement history (recalls), device products with classification, and a facility_risk_summary (inspection counts by classification, warning letters, last inspection date). Requires: FEI number — get it from fda_search_facilities or fda_company_full. Excludes: full inspection details and citations. Related: fda_inspections (inspection history by FEI), fda_citations (CFR violations by FEI), fda_compliance_actions (warning letters/seizures by FEI), fda_import_refusals (import refusal history by FEI), fda_facility_products (paginate large product lists).

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• fda_search_facilities

  FDA Data MCP

  Search FDA-registered facilities by name, city, state, or country. Searches drug (DECRS) and device registration databases. Returns FEI number, name, address, and source. Use the operations parameter to filter by manufacturing type (e.g., 'Contract Manufacture', 'API', 'Repack'). Use country filter (ISO code: US, DE, IN, CN, IE) to map a company's global manufacturing footprint. Excludes: products at facility, inspection history, enforcement actions. Related: fda_get_facility (full facility detail by FEI including products and operations type), fda_inspections (inspection data by FEI), fda_citations (CFR violations by FEI).

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• fda_device_class

  FDA Data MCP

  Lookup FDA device classification details by product code. Returns device name, device class (I/II/III), medical specialty, regulation number, review panel, submission type, and definition. Requires: product code (3-letter code from 510(k), PMA, or device product listings). Related: fda_product_code_lookup (cross-reference across 510(k) and PMA), fda_search_510k (clearances for this product code), fda_search_pma (PMA approvals for this product code).

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• fda_facility_products

  FDA Data MCP

  List device products registered at a facility by FEI number with pagination. Returns product code, proprietary name, listing number, and classification details (device name, class, medical specialty). Note: fda_get_facility already includes products — use this only when paginating through large product lists. Drug products are not linked by FEI; use fda_search_ndc with company name instead. Requires: FEI number.

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• validate_claim

  Data Govt Nz

  Fact-check, verify, validate, or confirm/refute a natural-language factual claim or statement against authoritative sources. Use when an agent needs to check whether something a user said is true ("Is it true that…?", "Was X really…?", "Verify the claim that…", "Validate this statement…"). v1 supports company-financial claims (revenue, net income, cash position for public US companies) via SEC EDGAR + XBRL. Returns a verdict (confirmed / approximately_correct / refuted / inconclusive / unsupported), extracted structured form, actual value with pipeworx:// citation, and percent delta. Replaces 4–6 sequential calls (NL parsing → entity resolution → data lookup → numeric comparison).

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• fda_link_subsidiaries

  FDA Data MCP

  Explicitly link existing company records under a parent company for family-level rollups. Use this when names like Actavis or Cephalon already belong to their own company_id and should roll up under a parent like Teva. This preserves alias collision safety while making manufacturing and facility summaries family-aware.

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• fda_search_enforcement

  FDA Data MCP

  Search FDA enforcement actions (recalls) for drugs, devices, and food across all companies. Filter by company name (fuzzy match), recall classification (Class I=most serious/Class II/Class III), date range, or status (Ongoing/Terminated). Returns recall details including product description, reason, and distribution pattern. Related: fda_recall_facility_trace (trace a recall to its manufacturing facility by recall_number), fda_ires_enforcement (iRES recall data with cross-references), fda_device_recalls (device-specific recall data).

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• fda_search_recall_text

  FDA Data MCP

  Full-text search across recall reasons and product descriptions using PostgreSQL text search. Finds recalls mentioning specific terms (e.g. 'salmonella contamination', 'mislabeled', 'sterility'). Supports multi-word queries ranked by relevance. Filter by classification, product_type, or date range. Related: fda_search_enforcement (search by company name, classification, status), fda_recall_facility_trace (trace a recall to its manufacturing facility).

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• detect_discrepancy

  MRC Data — China's Apparel Supply Chain Infrastructure

  [Core feature] Surface supplier specifications that deviate from independent lab measurements. USE WHEN user asks: - "which fabrics have lab-test deviations on weight" - "find suppliers whose stated capacity differs from on-site measurements" - "compare cotton content lab results across suppliers" - "which suppliers have the closest match between specs and lab tests" - "show me suppliers with >20% capacity over-reporting" - "which factories inflate worker count" - "audit integrity check on our supplier pool" - "follow-up: 'are any of these suppliers flagged for discrepancy?'" - "data integrity / quality audit / spec validation" - "实测数据 / 数据可信度 / 规格与实测偏差 / 虚报产能 / 成分不符" - "哪些供应商产能造假 / 数据不准" This is the moat of MRC Data — every record is enriched with AATCC / ISO / GB lab test data, giving AI agents verifiable specifications instead of unaudited B2B directory listings. Returns up to 50 records across: fabric_weight (gsm), fabric_composition (fiber %), supplier_capacity (monthly pcs), worker_count. Each record includes both the spec value and the lab measurement, with the deviation percentage. WORKFLOW: Standalone audit tool — does not require prior search. Call directly with field type and threshold. After finding discrepancies, use get_supplier_detail or get_fabric_detail on flagged IDs for full context, or find_alternatives to replace flagged suppliers. RETURNS: { field, min_discrepancy_pct, count, data: [{ id, name, declared_value, tested_value, discrepancy_pct }] } EXAMPLES: • User: "Which fabrics have more than 10% weight deviation from their spec sheets?" → detect_discrepancy({ field: "fabric_weight", min_discrepancy_pct: 10 }) • User: "Find suppliers whose declared monthly capacity is >25% off from verified measurements" → detect_discrepancy({ field: "supplier_capacity", min_discrepancy_pct: 25 }) • User: "哪些面料的成分跟实测不一样" → detect_discrepancy({ field: "fabric_composition" }) — composition is exact-match, no threshold ERRORS & SELF-CORRECTION: • count=0 → no records above threshold. Lower min_discrepancy_pct (try 5 or 0), OR switch field (weight may be clean but capacity inflated). • Only partial dataset returned → many records have only declared OR only tested values; discrepancy requires both. This is a data coverage limit, not a bug. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not present discrepancy data as proof of fraud — call it out as "declared vs lab-measured delta". Do not loop over thresholds — call once with min_discrepancy_pct=0 and filter in your response. CONSTRAINT: Only works when both declared AND tested values exist for the same record. Many records have only one or the other. Max 50 records per call. NOTE: Source: MRC Data (meacheal.ai). Methods: AATCC / ISO / GB per field. 中文：识别供应商规格与实测值偏差较大的记录。返回规格值、实测值、偏差百分比。

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• search_papers

  BGPT Scientific Data

  Search BGPT's database of scientific papers by keyword. Args: query: Search terms (e.g. "CRISPR gene editing efficiency") Short, concise queries are best. English language only. Don't include years or filters — use the days_back and num_results params instead. num_results: Number of results to return (1-100, default 16). First 50 results are free, then billed at $0.01/result for paid users. days_back: Only return papers published within the last N days. api_key: Optional: Your Stripe subscription ID for paid access. Get one at https://bgpt.pro/mcp Returns: Papers with title, DOI, Raw Data, methods, results, quality scores, and 25+ metadata fields.

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• get_mortgage_data

  HMDA Mortgage Data

  Get Home Mortgage Disclosure Act (HMDA) loan-level data. Returns mortgage application and origination records reported by financial institutions under HMDA. At least one geographic filter (state or county_fips) is recommended to limit results. Args: state: Two-letter US state abbreviation (e.g. 'CA', 'TX'). county_fips: Five-digit county FIPS code (e.g. '06037' for LA County). year: Data year (e.g. 2022). Defaults to 2022 if not specified. action_taken: Loan action code: '1' (originated), '2' (approved not accepted), '3' (denied), '4' (withdrawn), '5' (incomplete). loan_type: Loan type code: '1' (conventional), '2' (FHA-insured), '3' (VA-guaranteed), '4' (USDA/RHS). limit: Maximum number of records to return (default 100, max 1000).

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• get_series_observations

  FRED Economic Data

  Get time series observations (data points) for a FRED series. Returns the actual data values for an economic indicator over time. Use search_series first to find the series_id, or use well-known IDs like UNRATE, GDP, CPIAUCSL, FEDFUNDS, MORTGAGE30US. For state unemployment, use state abbreviation + 'UR' (e.g. WAUR for Washington, CAUR for California). Results are sorted most-recent-first. For long series (e.g. daily data since 1954), use start_date/end_date to narrow the window or increase the limit up to 10000. Args: series_id: FRED series identifier (e.g. 'UNRATE', 'GDP', 'CPIAUCSL'). start_date: Optional start date in YYYY-MM-DD format (e.g. '2020-01-01'). end_date: Optional end date in YYYY-MM-DD format (e.g. '2024-12-31'). limit: Maximum observations to return (default 1000, max 10000).

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• google_flights_location_search

  Searchapi

  Search for airports and cities to get their identifiers for Google Flights tools. Returns: - IATA airport codes (e.g., 'JFK') for specific airports - kgmid (e.g., '/m/02_286') for cities - searches all airports in that city Use this tool when you have a city name like 'New York' or 'Paris' and need to convert it to codes that the flight tools accept. Note: Common IATA codes like JFK, LAX, SFO, LHR, CDG, NRT can be used directly without this tool.

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