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269,766 tools. Last updated 2026-07-07 17:12

"namespace:io.github.GlobKurier-pl" matching MCP tools:

  • Search non-Czech business registries by company name. Supported: GB (Companies House), SK (ORSR/RPO), PL (KRS), NL/IT/AT/ES (GLEIF/LEI only; exact VAT data via lookup_company_by_vat or get_company with VAT), DE (GLEIF/LEI), FR (SIRENE), NO (BRREG), DK (CVR).
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  • 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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  • PLN exchange rate for one currency over time. Specify the table (A/B for mid-rate, C for bid/ask) and a 3-letter ISO 4217 code (e.g. USD, EUR, GBP, CHF, JPY). Defaults to the latest rate; optionally pass a single date, last_n recent points, or a start_date/end_date window (max ~93 days, working days only). Use this for one currency; use exchange_rate_table for the whole list.
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  • Cursor-paginated browse over the catalog. Quality-first: by default excludes questions flagged for review (use quality='all' for full pool). USE WHEN: full catalog sync, delta sync (updated_since), exhaustive enumeration by filter. NOT WHEN: you only need N random samples (use quizbase_random) or a single record (use quizbase_question_by_id). PAGINATION: stable cursor over id UUIDv7 DESC. First call: omit cursor. Next: pass meta.nextCursor. Stop when nextCursor is null. KEY FILTERS (full parity with REST): - lang: ISO 639-1, default "en". Supported: en, pl. - category (slug), difficulty (trivial|easy|medium|hard|expert — LLM-calibrated), type (multiple|boolean), subcategory (raw slug). - tags (AND), tags_any (OR, max 10): raw tag slugs. - topic (curated, alias resolver), topics_any (OR over curated): higher precision than tags. - regions (cultural affinity, AND): empty = no cultural advantage assumed. Lowercase ISO 3166-1 alpha-2 ('us', 'pl', 'gb') + cultural codes ('jewish', 'christian-catholic', 'islam'). Filter for content statistically more likely known by residents/members. Discover via quizbase_regions. - source (array): include only these of 12 (opentdb, opentriviaqa, kqa-pro, entityq, mintaka, mkqa, nq-open, creak, qasc, arc, webq, quizbase). - exclude_source (array): drop these sources, e.g. ["entityq"]. Applied after source. - license (SPDX): e.g. CC-BY-SA-4.0, MIT. - quality: 'high' (default) = cleanest, most broadly-useful. 'standard' = broader pool incl. niche/too-specific. 'all' = full pool incl. flagged; when 'all', each question gains a "quality" field ('high' or 'needs_review'). - updated_since (ISO 8601): only questions updated after this — for delta sync caches. BATCH + TRANSLATION MAPPING: - ids (up to 250): fetch those exact records in one call (anti-repeat, deep-links, restoring a saved set). Terminal selector — browse filters and cursor are ignored. Missing ids → meta.missing. - content_language (en|pl): with ids, returns each question's sibling in that CONTENT language across the translation chain — the same questions in another language. Distinct from lang (labels only). PAGINATION + COUNTING: - cursor (string): from previous meta.nextCursor. Omit for page 1. - limit (1-100, default 20). - count: none (default, skip — page via nextCursor) | exact (precise COUNT(*), index-only ~25-90ms). OUTPUT: { questions: [...], meta: { count, countMode, language, nextCursor, total? } }. Each question carries full per-record attribution (source, author, license, licenseVersion, licenseUrl, sourceId, url, modifications, lastModified) — identical shape to REST /api/v1/questions. ATTRIBUTION REQUIRED if you redistribute. Credit each question using its own attribution object — see license + licenseUrl + modifications fields per record. COMMON MISTAKES: not passing the cursor on subsequent calls (you'll re-read page 1); polling without updated_since when doing delta sync.
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  • Public catalog counters with live breakdowns by language, source, category, difficulty, topic, tag. USE WHEN: showing catalog overview, picking a category programmatically, building landing copy, deciding "do we have enough X-content for this quiz". OUTPUT FIELDS: - total: approved questions in 'en' + 'pl'. - byLanguage: { en: N, pl: N }. - bySource: { entityq: N, mintaka: N, 'kqa-pro': N, ... } — 12 keys, one per source database. - byDifficulty: { trivial: N, easy: N, medium: N, hard: N, expert: N, unrated: N } — null difficulty mapped to 'unrated'. trivial/expert populated by LLM calibration. - byCategory: top 24 with localized names. - byTopic / byTag: top 30 curated topics + top 30 tags with localized labels. - meta: { generatedAt: ISO 8601, language }. INPUTS: lang (default "en") affects byCategory[].name and byTopic[].label / byTag[].label. DATA FRESHNESS: snapshot regenerated daily (~03:00 UTC) + on demand after batch imports. generatedAt shows when. Counts stable ±0.01% between snapshots. COMMON MISTAKES: polling stats every request (cache it on your side; 5-min Redis TTL on ours); treating bySource keys as stable enum (use quizbase_languages / quizbase_categories for canonical input enums).
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  • Multi-language, multi-source web search that goes beyond Anglo-centric results. Supports 15 languages (fr/de/es/it/pt/nl/ja/zh/ko/ar/ru/sv/pl/tr/en) with automatic detection. Aggregates results from Mojeek (independent search engine, multilang) and Wikipedia (native multilang API), with DDG and HN as English-language complements. Returns deduplicated results ranked by cross-engine consensus. Use when you need non-English search results, when DDG fails, or for geographically-biased queries. Phase 2 #7 of the geo/lang expansion plan. Note: Brave/Bing/Searx are blocked from DO IPs — configure AICI_RESEARCH_PROXY_URL for residential proxy.
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  • Narodowy Bank Polski (National Bank of Poland) Web API MCP. Keyless.

  • dane.gov.pl — Poland's national open data portal (Otwarte Dane).

  • "Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO, news, GLEIF and returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first if you only have a name).
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  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).
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  • "Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO, news, GLEIF and returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first if you only have a name).
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  • "What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since `since`), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). `since` accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.
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  • 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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  • ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1241 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 4,770 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Expect 15-60s.
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  • Realizable-vs-theoretical edge check against live CLOB order-book depth. REQUIRES one of `market` (single-market mode) or `event` (basket/partition mode). SINGLE-MARKET: pass a market slug/URL + side (buy_yes|sell_yes|buy_no|sell_no, default buy_yes) + size_usd (default 1000 — max spend on buys, target proceeds on sells); walks the ladder and returns top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, and a verdict (clean|degraded|cannot_fill). BASKET: pass an event slug/URL + side (sell_yes = capture overround by selling every leg, buy_yes = capture underround; default auto from partition sum) + size_usd interpreted as settlement notional S (shares per leg; each share pays $1); returns theoretical_sum vs realizable_sum (top-of-book vs VWAP across all legs), capture_ratio, profit_usd at executed size, per-leg fill detail, thin_legs[], max_clean_notional_usd, and forced_directional_risk naming the legs most likely to strand you unhedged. USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500 — theoretical overround on thin books is not capturable, and partial basket fills convert an arb into an unhedged directional position (the dominant loss mode in real arb-bot P&L).
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  • Lista votações em comissões. O parâmetro `por` (padrão `comissao`) define o eixo da consulta: `por: comissao` → exige `siglaComissao`; lista as votações daquela comissão. `por: senador` → exige `codigoSenador`; lista os votos do senador em comissões (filtro opcional `comissao`). `por: materia` → exige `sigla`, `numero` e `ano` (ex.: PL 2630/2020); lista as votações da proposição em comissões (filtro opcional `comissao`). Em todos os casos aceita período opcional `dataInicio`/`dataFim` (YYYYMMDD, filtrado pela data da reunião) e retorna `{ por, ...contexto, count, votacoes }`, cada votação com `codigo`, `data`, `comissao`, `reuniao`, `materia`, `descricao`, totais computados dos votos (`totalSim`/`totalNao`/`totalAbstencao`) e `votos` (senador, partido, voto). Sem paginação. Obtenha siglas via `senado_listar_comissoes`, `codigoSenador` via `senado_listar_senadores`; para votações no plenário use `senado_votos_materia`.
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  • Consulta tabelas de referência do Senado pelo parâmetro `tabela`. Valores: `tipos-materia` → `{ count, tipos }` (sigla/nome/descricao dos tipos de proposição, p.ex. PEC, PL, MPV) — use para achar a `sigla` correta antes de `senado_buscar_materias`/`senado_search_processos`; `partidos` → `{ count, totalSenadores, partidos }` (partidos com bancada atual, ordenados por nº de senadores); `ufs` → `{ count, totalSenadores, ufs }` (as 27 UFs com a contagem de senadores em exercício); `legislatura-atual` → `{ numero, periodo, dataInicio, dataFim }` da legislatura vigente; `tipos-norma` → `{ count, tipos }` (sigla/descricao dos tipos de norma para `senado_buscar_legislacao`); `tipos-uso-palavra` → `{ count, tipos }` (codigo/descricao para interpretar `tipoUsoPalavra` em `senado_discursos_senador`). Toda resposta inclui o campo `tabela`. Para a relação nominal de parlamentares use `senado_listar_senadores`.
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  • Formats a number using the locale conventions of a specific European country, applying the correct decimal separator and thousands separator. Returns { original: number, formatted: string, locale: string, country_code: string }. Different European countries use different conventions — Portugal and most of continental Europe use '1.234,56' (dot as thousands, comma as decimal), while Ireland uses '1,234.56'. Supports PT, ES, FR, DE, IT, NL, BE, PL, SE, DK, FI, AT, IE, GR, HU, RO. Use when displaying prices, measurements, or any numeric value to end users in a specific European country.
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  • Look up a Legal Entity Identifier (LEI) via GLEIF — the global standard for entity identification. Returns legal name, registered address, status, parent + ultimate parent relationships, and child entities (subsidiaries). Also supports reverse lookup from a national company number to LEI across 15 countries (DK, NO, SE, FI, IE, UK, FR, DE, CZ, PL, LV, EE, NL, BE, LU). Tier note (reverse mode only): NL and DE use paid upstream registries — free-tier API keys receive HTTP 402 'upgrade_required'; do NOT retry on 402.
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  • Fetch N random trivia questions matching filters. Quality-first: by default excludes questions flagged for review (use quality='all' to include for audit/research). USE WHEN: building a quiz, sampling content for warmup, generating practice sets. NOT WHEN: you need a specific question ID (use quizbase_question_by_id) or want to explore a topic deeply with facets (use quizbase_topic_by_slug). KEY FILTERS: - amount: 1-50, default 10. - lang: ISO 639-1. Default "en". Supported: en, pl. Strict — unknown language returns 400. - category (slug): e.g. geography, history, science-and-nature. Full list via quizbase_categories. - difficulty: trivial | easy | medium | hard | expert. LLM-calibrated. Records not yet LLM-rated hold the importer placeholder (mostly "medium" for factoid sources). - type: multiple | boolean (default both; no text_input in random). - regions (cultural affinity, AND): empty in data = no cultural advantage assumed. Lowercase ISO 3166-1 alpha-2 ('us', 'pl', 'gb') + cultural codes ('jewish', 'christian-catholic', 'islam'). Filter for content statistically more likely known by residents/members. Discover via quizbase_regions. - source (array): include only these source databases (one or more of 12: opentdb, opentriviaqa, kqa-pro, entityq, mintaka, mkqa, nq-open, creak, qasc, arc, webq, quizbase). - exclude_source (array): drop these sources, e.g. ["entityq"] for human-curated only. Applied after source. - license (SPDX): CC-BY-SA-4.0 | CC-BY-SA-3.0 | MIT | etc. Restrict to redistribution-friendly content. - topic (curated slug): higher precision than tags. Alias resolver matches subcategories+tags. List via quizbase_topics. - topics_any: OR over curated topics, max 10. - tags (AND), tags_any (OR), subcategory: raw taxonomy. Use topic if available. - quality: 'high' (default, recommended) = cleanest, most broadly-useful. 'standard' = broader pool incl. niche/too-specific (more volume). 'all' = audit/research, includes flagged — when 'all', each question gains a "quality" field ('high' or 'needs_review'). - exclude (UUIDs, max 250): de-dupe within a quiz session. OUTPUT: { questions: [...], meta: { count, language } }. Each question carries full per-record attribution (source, author, license, licenseVersion, licenseUrl, sourceId, url, modifications, lastModified) — identical shape to REST /api/v1/questions/random. ATTRIBUTION REQUIRED if you redistribute. CC-BY-SA modifications must be credited per § 3(a)(1)(B) using each question's own attribution object. COMMON MISTAKES: forcing lang='pl' for a global audience (use 'en' default); skipping quality (default already excludes flagged content — only pass quality='all' for audit); using tags when a curated topic exists (worse precision).
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  • "Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.
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