MCP server for trivia: 1.4M+ questions (EN+PL), 24 categories, 12 tools + 4 prompts, OAuth 2.1.
Inferido de los transportes que declara este listado (streamable-http). Que un cliente no aparezca aquí no significa que se haya descartado: simplemente Forge no puede confirmarlo.
La verificación confirma la identidad del publicador (la propiedad del repo), no la seguridad del código. El análisis de seguridad cubre los CVE conocidos y los scripts de instalación sospechosos.
Leído de un handshake MCP real initialize → tools/list contra el endpoint declarado. No se invocó ninguna herramienta: tools/list es la llamada de introspección de solo lectura que el protocolo define para esto. Refleja lo que el servidor anunciaba en ese momento; un endpoint alojado no está fijado a ninguna versión y puede cambiar sin avisar.
https://quizbase.runriva.com/mcp12 herramientas · 2065 msquizbase_randomFetch 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).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).
No se publicó ningún esquema de entrada para esta herramienta.
quizbase_listCursor-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.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.
No se publicó ningún esquema de entrada para esta herramienta.
quizbase_question_by_idFetch one question with FULL per-record attribution (source, author, license, modifications, lastModified, sourceId, url) and `quality: "high" | "needs_review"` (always present — deep-link semantic means full row). USE WHEN: deep link to a question, full provenance lookup for redistribution, cache refresh, moderation inspection. INPUTS: id (UUID), lang (affects category.name and label translations only). 404 returned via {question: null, error: "not_found"} — id may be invalid, pending/rejected, canonical-duplicate, or tombstoned.Fetch one question with FULL per-record attribution (source, author, license, modifications, lastModified, sourceId, url) and `quality: "high" | "needs_review"` (always present — deep-link semantic means full row). USE WHEN: deep link to a question, full provenance lookup for redistribution, cache refresh, moderation inspection. INPUTS: id (UUID), lang (affects category.name and label translations only). 404 returned via {question: null, error: "not_found"} — id may be invalid, pending/rejected, canonical-duplicate, or tombstoned.
No se publicó ningún esquema de entrada para esta herramienta.
quizbase_statsPublic 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).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).
No se publicó ningún esquema de entrada para esta herramienta.
quizbase_topicsDiscover curated topics (2,184 entries with aliases). USE WHEN: planning a multi-round quiz, exploring "what is available about X", showing topic browser. Sorted by count DESC, slug ASC. Cursor-paginated. INPUTS: q (substring on label/alias), kind (tag|subcategory), cursor, limit (max 500).Discover curated topics (2,184 entries with aliases). USE WHEN: planning a multi-round quiz, exploring "what is available about X", showing topic browser. Sorted by count DESC, slug ASC. Cursor-paginated. INPUTS: q (substring on label/alias), kind (tag|subcategory), cursor, limit (max 500).
No se publicó ningún esquema de entrada para esta herramienta.
quizbase_topic_by_slugFetch one curated topic with facets (byCategory, byDifficulty, byLanguage, coOccurringTags, coOccurringSubcategories) and 3 sample questions. USE WHEN: zooming into a topic, deciding multi-round quiz structure. Returns {topic: null, error: "not_found"} when slug is unknown.Fetch one curated topic with facets (byCategory, byDifficulty, byLanguage, coOccurringTags, coOccurringSubcategories) and 3 sample questions. USE WHEN: zooming into a topic, deciding multi-round quiz structure. Returns {topic: null, error: "not_found"} when slug is unknown.
No se publicó ningún esquema de entrada para esta herramienta.
quizbase_tagsRaw tag dump (10k+ entries) with display label and question count. USE WHEN: building a tag picker, searching "is X a tag", running analytics. Curated higher-level groupings → quizbase_topics. INPUTS: q (substring), cursor, limit (max 500).Raw tag dump (10k+ entries) with display label and question count. USE WHEN: building a tag picker, searching "is X a tag", running analytics. Curated higher-level groupings → quizbase_topics. INPUTS: q (substring), cursor, limit (max 500).
No se publicó ningún esquema de entrada para esta herramienta.
quizbase_subcategoriesRaw subcategory dump (LLM-organic kebab-case, middle taxonomy layer between category and tags) with display label and count. USE WHEN: navigating between top-level category and individual tags, exploring topic structure. Filter questions via quizbase_random?subcategory=<slug>. INPUTS: q, cursor, limit (max 500).Raw subcategory dump (LLM-organic kebab-case, middle taxonomy layer between category and tags) with display label and count. USE WHEN: navigating between top-level category and individual tags, exploring topic structure. Filter questions via quizbase_random?subcategory=<slug>. INPUTS: q, cursor, limit (max 500).
No se publicó ningún esquema de entrada para esta herramienta.
quizbase_categoriesList of 24 top-level categories with i18n labels. USE WHEN: building a category picker, validating ?category= input. Stable enum (rarely changes). For higher-resolution browsing → quizbase_subcategories or quizbase_topics.List of 24 top-level categories with i18n labels. USE WHEN: building a category picker, validating ?category= input. Stable enum (rarely changes). For higher-resolution browsing → quizbase_subcategories or quizbase_topics.
No se publicó ningún esquema de entrada para esta herramienta.
quizbase_languagesReturns supported language whitelist (ISO 639-1) with question counts per language. USE WHEN: showing language picker, validating ?lang= input, deciding fallback. Day 1: en + pl.Returns supported language whitelist (ISO 639-1) with question counts per language. USE WHEN: showing language picker, validating ?lang= input, deciding fallback. Day 1: en + pl.
No se publicó ningún esquema de entrada para esta herramienta.
quizbase_regionsDiscover region codes used by the catalog. **Cultural affinity** — a question is tagged with a region if residents of that country, or members of that cultural/religious group, are statistically more likely to know the answer (NOT geography of the subject). USE WHEN: planning a quiz targeting users from a specific country or cultural background, exploring "what regions are represented". OUTPUT: array of {code, kind, label, count} sorted by count DESC. INPUTS: lang (en|pl), q (substring on code/label), kind (country|cultural), cursor, limit (max 500). Pair with quizbase_random or quizbase_list using `regions:[...]` to fetch matching questions.Discover region codes used by the catalog. **Cultural affinity** — a question is tagged with a region if residents of that country, or members of that cultural/religious group, are statistically more likely to know the answer (NOT geography of the subject). USE WHEN: planning a quiz targeting users from a specific country or cultural background, exploring "what regions are represented". OUTPUT: array of {code, kind, label, count} sorted by count DESC. INPUTS: lang (en|pl), q (substring on code/label), kind (country|cultural), cursor, limit (max 500). Pair with quizbase_random or quizbase_list using `regions:[...]` to fetch matching questions.
No se publicó ningún esquema de entrada para esta herramienta.
quizbase_reportSubmit a content correction, copyright concern, or factual error report. USE WHEN: user (via your interface) flags a wrong answer, broken translation, attribution issue, or DMCA concern. INPUTS: at least one of (questionId UUID, questionText, questionUrl), type (translation|factual|inappropriate|attribution|other), comment (optional, max 2000), reporterEmail (optional). OUTPUT on success: {ok:true, reportId}. On failure the result is marked isError:true with structuredContent {error, message} — error codes: invalid_input, not_found, rate_limit_exceeded (per-IP 5/min), internal_error.Submit a content correction, copyright concern, or factual error report. USE WHEN: user (via your interface) flags a wrong answer, broken translation, attribution issue, or DMCA concern. INPUTS: at least one of (questionId UUID, questionText, questionUrl), type (translation|factual|inappropriate|attribution|other), comment (optional, max 2000), reporterEmail (optional). OUTPUT on success: {ok:true, reportId}. On failure the result is marked isError:true with structuredContent {error, message} — error codes: invalid_input, not_found, rate_limit_exceeded (per-IP 5/min), internal_error.
No se publicó ningún esquema de entrada para esta herramienta.
12 de 12 herramientas publicaron una descripción.
Los nombres y descripciones de las herramientas los escribe el publicador y se muestran literalmente como texto inerte. Son las cadenas que un cliente MCP pasa al modelo, así que Forge las analiza en busca de patrones de inyección de prompts — cualquier hallazgo aparece junto al análisis de seguridad de arriba. «Privilegiada» es una coincidencia de palabra clave en el nombre de la herramienta, no una auditoría de lo que hace: un nombre inofensivo puede hacer cualquier cosa.
MCP server for trivia: 1.4M+ questions (EN+PL), 24 categories, 12 tools + 4 prompts, OAuth 2.1.
Los nombres enlazados abren el índice de Forge con todas las entradas que se observó que exponen esa herramienta. Ver todas las herramientas indexadas.
Esta entrada no publica ningún paquete de npm, así que Forge no tiene un árbol de dependencias para ella. Es una carencia de cobertura, no una afirmación de que no tenga dependencias.