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com.moltlinestudio/research
serveur MCP (Model Context Protocol) · moltline-research 1.1.0
Référencé dans l'annuaire. Seul le pentest comportemental fait foi, et il n'a pas encore été exécuté sur ce serveur.
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Au dernier audit MCP Hub, le serveur MCP « com.moltlinestudio/research » est classé « Non encore testé ». Référencé dans l'annuaire. Seul le pentest comportemental fait foi, et il n'a pas encore été exécuté sur ce serveur. Le verdict est réévalué en continu ; consultez la fiche pour l'état à jour.
Méthode : MCP Hub analyse la description de chaque outil (couche 1) et, pour le verdict fort, exécute le serveur dans une micro-VM isolée avec leurres et réseau bloqué (couche 2). On publie des noms et des compteurs, jamais le contenu brut renvoyé par un outil.
Les 8 outils
- confidence_interval≈ 400 tokens
Compute a confidence interval for a mean (normal approximation). FREE. Typical input {"mean": 72.4, "std_dev": 8.1, "n": 64, "confidence_pct": 95} returns {"mean": 72.4, "margin_of_error": 1.9845, "interval": [70.4155, 74.3845], "note": "..."}. Use on data already collected, for a mean. Normal approximation, so it is unreliable on very small or heavily skewed samples. Not for proportions or two-group comparisons - the data server's ab_test compares two proportions. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "confidence 90/95/99, n>=2, std_dev>=0"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
Paramètres, retour & exemple (4)
Paramètresn· integer · requis
Sample size; at least 2.mean· number · requis
Sample mean.std_dev· number · requis
Sample standard deviation; 0 or greater.confidence_pct· number · optionnel
Confidence level; must be 90, 95, or 99. Default 95.
Exemple d'appel{"name": "confidence_interval", "arguments": {"n": 1, "mean": 1, "std_dev": 1}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - format_citation≈ 523 tokens
Format a citation in APA 7, MLA 9, or Chicago author-date style. FREE. Typical input {"style": "apa", "authors": ["Curie, Marie"], "year": 1911, "title": "Radium and radioactivity", "container": "Century Magazine"} returns {"style": "apa", "citation": "Curie, M. (1911). Radium and radioactivity. Century Magazine.", "note": "..."}. Use when the source details are already known and only the formatting is missing. Not for finding or verifying a source. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "style must be apa, mla, or chicago"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
Paramètres, retour & exemple (8)
Paramètresurl· string · optionnel
Optional URL of the source.year· integer · requis
Publication year, e.g. 2024.style· string · requis
Citation style: "apa", "mla", or "chicago" (case-insensitive).title· string · requis
Title of the work being cited.authors· array · requis
Authors as "Last, First" strings in source order, at least one, e.g. ["Curie, Marie"].accessed· string · optionnel
Optional access date for MLA web sources, e.g. "12 Aug. 2026".container· string · optionnel
Optional journal, book, or site name.publisher· string · optionnel
Optional publisher name.
Exemple d'appel{"name": "format_citation", "arguments": {"year": 1, "style": "texte", "title": "texte", "authors": []}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - get_free_skill≈ 340 tokens
Load a product's free gateway skill with its complete instructions. FREE. Typical input {"slug": "thesis-advisor"} returns {"slug": ..., "skill": "<skill name>", "instructions": "<full skill text>"}. Returns exactly one skill - the product's free gateway skill - chosen automatically from the slug, with no plan required. Use when the caller wants usable instructions immediately. Not for the product's other skills: those are named and need get_full_skill with a skill_name, which requires a paid plan. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "unknown slug '<value>'. Use list_products."}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
Paramètres, retour & exemple (1)
Paramètresslug· string · requis
Product slug exactly as returned by list_products, e.g. "thesis-advisor".
Exemple d'appel{"name": "get_free_skill", "arguments": {"slug": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - get_full_product≈ 332 tokens
Load one product in full: its persona plus every paid skill. PREMIUM (license). Typical input {"slug": "thesis-advisor"} returns {"slug": ..., "name": ..., "persona": "<persona text>", "skills": [{"name": ..., "instructions": ...}, ...], "free_skill": {...}}. Returns persona plus every skill for one product. Use when the caller wants the whole product. Not for a single skill (get_full_skill) and not for a free look, which list_products and get_free_skill provide with no plan. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "unknown slug '<value>'"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
Paramètres, retour & exemple (1)
Paramètresslug· string · requis
Product slug exactly as returned by list_products, e.g. "thesis-advisor".
Exemple d'appel{"name": "get_full_product", "arguments": {"slug": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - get_full_skill≈ 353 tokens
Load one paid skill's complete instructions from a product. PREMIUM (license). Typical input {"slug": "thesis-advisor", "skill_name": "Outline Builder"} returns {"slug": ..., "skill": ..., "instructions": "<full skill text>"}. Returns one named skill, selected by skill_name. Use when the caller wants one specific paid skill. Not for the free gateway skill, which get_free_skill returns with no plan, and not for every skill at once (get_full_product). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "unknown slug '<value>'"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
Paramètres, retour & exemple (2)
Paramètresslug· string · requis
Product slug exactly as returned by list_products.skill_name· string · requis
Exact skill name as listed in that product's "skills" array from list_products.
Exemple d'appel{"name": "get_full_skill", "arguments": {"slug": "texte", "skill_name": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - list_products≈ 353 tokens
List every product in the Research Desk line with its included skills. FREE. Takes no arguments. Returns a list of 7 product objects, each {"slug": "thesis-advisor", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
Paramètres, retour & exemple (0)
Exemple d'appel{"name": "list_products", "arguments": {}}Exemple de retour{"content": [{"type": "text", "text": "…"}], "structuredContent": {"result": []}} - sample_size≈ 398 tokens
Calculate the survey sample size needed for a confidence level and margin. FREE. Uses maximum variance (p=0.5) with a finite-population correction when population is given. Typical input {"population": 5000, "confidence_pct": 95, "margin_pct": 5} returns {"required_sample": 357, "assumptions": "p=0.5 (max variance), random sampling"}. Use before collecting data, to size a survey. Not for analyzing data already collected (stats_describe, confidence_interval). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "confidence_pct must be 90, 95, or 99"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
Paramètres, retour & exemple (3)
Paramètresmargin_pct· number · optionnel
Acceptable margin of error percentage; above 0 and at most 50. Default 5.population· integer · optionnel
Total population size; 0 (default) means unknown or very large.confidence_pct· number · optionnel
Confidence level; must be 90, 95, or 99. Default 95.
Exemple d'appel{"name": "sample_size", "arguments": {"margin_pct": 1, "population": 1, "confidence_pct": 1}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - stats_describe≈ 320 tokens
Describe a numeric dataset: center, spread, quartiles, and outliers. FREE. Typical input {"numbers": [12, 15, 14, 90, 13]} returns {"n": 5, "mean": 28.8, "median": 14.0, "std_dev": ..., "min": 12, "max": 90, "q1": ..., "q3": ..., "iqr_outliers": [90], "skew": "right (mean > median)"}. Use as a first summary of one numeric dataset. Not for interval estimates (confidence_interval) and not for planning a study (sample_size). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "no numbers"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
Paramètres, retour & exemple (1)
Paramètresnumbers· array · requis
The dataset as a list of numbers; at least 1 value.
Exemple d'appel{"name": "stats_describe", "arguments": {"numbers": []}}Exemple de retour{"content": [{"type": "text", "text": "…"}]}
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