QuizBase

com.runriva.quizbase/mcpVersion 0.1.1

MCP server for trivia: 1.4M+ questions (EN+PL), 24 categories, 12 tools + 4 prompts, OAuth 2.1.

Status

Responds285 msNov 14, 2026, 14:13 UTCAnswered our handshake without sign-in.

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Last checked: Nov 14, 2026, 14:13 UTC
Latency: 285 ms
Remotes responding: 1 of 1
Sign-in: API key
Hosting: Hosted outside the EU (detected)
Registry data as of: Nov 14, 2026, 22:14 UTC

Data from the official MCP Registry, checked by run.zero. How we check

Connect

Streamable HTTP

https://quizbase.runriva.com/mcpResponds285 msNov 14, 2026, 14:13 UTC

No sign-in

Claude Code

claude mcp add --transport http quizbase https://quizbase.runriva.com/mcp --header 'Authorization: Bearer <YOUR_TOKEN>'

Replace <YOUR_TOKEN> before running.

Claude Desktop and claude.ai

Settings > Connectors > Add custom connector
Name: quizbase
Remote MCP server URL: https://quizbase.runriva.com/mcp
This server expects the header Authorization.

Cursor

{
  "mcpServers": {
    "quizbase": {
      "url": "https://quizbase.runriva.com/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_TOKEN>"
      }
    }
  }
}

Replace <YOUR_TOKEN> before running.

VS Code

code --add-mcp '{"name":"quizbase","type":"http","url":"https://quizbase.runriva.com/mcp","headers":{"Authorization":"Bearer <YOUR_TOKEN>"}}'

Replace <YOUR_TOKEN> before running.

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Tools

12 tools

Tools of QuizBase
	Description		Read-only	Idempotent	Open world
`quizbase_categories`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.	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	Yes	Yes	No
`quizbase_languages`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.	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	Yes	Yes	No
`quizbase_list`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 s	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 s	No	Yes	Yes	No
`quizbase_question_by_id`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.	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	Yes	Yes	No
`quizbase_random`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	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	No	Yes	No	No
`quizbase_regions`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.	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	Yes	Yes	No
`quizbase_report`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.	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	No	No	No
`quizbase_stats`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).	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	Yes	Yes	No
`quizbase_subcategories`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).	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	Yes	Yes	No
`quizbase_tags`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).	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	Yes	Yes	No
`quizbase_topic_by_slug`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.	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	Yes	Yes	No
`quizbase_topics`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).	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	Yes	Yes	No

Details

Registry status: Active
Published: May 24, 2026
Updated: May 24, 2026
Website: https://quizbase.runriva.com/docs/sdks/mcp-server⁠ (opens in a new tab)
Repository: Not given
Categories (suggested): AI modelsSuggested categories are assigned automatically from the registry text and may be wrong. Verified operators can correct them.
GDPR: Not declared

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