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ai.flyvolo/knowledge
serveur MCP (Model Context Protocol) · volo-knowledge 0.1.0
Référencé dans l'annuaire. Seul le pentest comportemental fait foi, et il n'a pas encore été exécuté sur ce serveur.
Est-ce que ai.flyvolo/knowledge est sûr ?
Au dernier audit MCP Hub, le serveur MCP « ai.flyvolo/knowledge » 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 19 outils
- describe_coverage≈ 136 tokens
What VOLO covers and what it does not: the full list of covered occupations and degrees (slug and name), which occupations have no evidence yet, and the counts. Call this when someone asks whether their job is covered, and whenever resolve_occupation_or_major returns null — then decide from the list which entry, if any, the person means. The answer is a fact about this site rather than a guess about their job.
Paramètres, retour & exemple (1)
Paramètreslocale· string · optionnel
Exemple d'appel{"name": "describe_coverage", "arguments": {"locale": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - find_affected≈ 60 tokens
Which occupation and which specific tasks a change record bears on.
Paramètres, retour & exemple (2)
Paramètresid· string · requislocale· string · optionnel
Exemple d'appel{"name": "find_affected", "arguments": {"id": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - find_evidence≈ 114 tokens
Verified evidence records for an occupation, optionally for one task. Each record carries its scope (where it applies), its stage, whether that stage can move a task judgement at all, and its source tier. Repeat the scope rather than smoothing it away.
Paramètres, retour & exemple (3)
Paramètresslug· string · requislocale· string · optionneltaskId· string · optionnel
Exemple d'appel{"name": "find_evidence", "arguments": {"slug": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - find_majors_for_occupation≈ 57 tokens
Which degrees lead into this occupation.
Paramètres, retour & exemple (2)
Paramètresslug· string · requislocale· string · optionnel
Exemple d'appel{"name": "find_majors_for_occupation", "arguments": {"slug": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - find_notes≈ 147 tokens
VOLO's long-form answers to the big questions — how many jobs AI has actually taken, what actually gets automated, how long someone has, what AI law already changed, where AI lands in a company. Call this FIRST for any question that is about the whole picture rather than one occupation: those are exactly the questions you can answer fluently without evidence, and these notes are the evidence. Each result carries the note's own limits.
Paramètres, retour & exemple (2)
Paramètresquery· string · optionnellocale· string · optionnel
Exemple d'appel{"name": "find_notes", "arguments": {"query": "texte", "locale": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - find_notes_for_occupation≈ 81 tokens
Which notes argue from this occupation's own records or task judgements. Use it to point someone from their own page to the wider answer.
Paramètres, retour & exemple (2)
Paramètresslug· string · requislocale· string · optionnel
Exemple d'appel{"name": "find_notes_for_occupation", "arguments": {"slug": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - find_transition_paths≈ 100 tokens
Options for someone in this occupation. Every path carries its real constraints (time, pay cut, seniority) and one action they can take this week that produces information. Never present a path without its constraint.
Paramètres, retour & exemple (2)
Paramètresslug· string · requislocale· string · optionnel
Exemple d'appel{"name": "find_transition_paths", "arguments": {"slug": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - get_action_brief≈ 263 tokens
Use this when a person asks what they should do about AI or automation in their job ("I'm an accountant, how do I stay employable?"). One call returns, task by task: where the task is heading and how strong the evidence is; which laws, regulators, courts or collective agreements keep that task (or its signature) with a person; which employers or regulators have already moved it; and transition paths, each with its real constraints and one thing to check this week. Pass the job title as the person said it (any language) or a slug; optionally the task ids they actually do. Build your advice on these facts, keep each record's scope and each task's limits, and never turn it into a probability, a score or a number of years.
Paramètres, retour & exemple (3)
Paramètreslocale· string · optionneltaskIds· array · optionneloccupation· string · requis
Job title in the person's words, or an occupation slug
Exemple d'appel{"name": "get_action_brief", "arguments": {"occupation": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - get_change≈ 78 tokens
One verified change record by id, with VOLO's reading: what it means, what it does not yet establish, and what a reader can verify themselves.
Paramètres, retour & exemple (2)
Paramètresid· string · requislocale· string · optionnel
Exemple d'appel{"name": "get_change", "arguments": {"id": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - get_change_history≈ 60 tokens
The verified change timeline for an occupation, oldest first.
Paramètres, retour & exemple (2)
Paramètresslug· string · requislocale· string · optionnel
Exemple d'appel{"name": "get_change_history", "arguments": {"slug": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - get_major≈ 85 tokens
A degree and the occupations it feeds. There is no score for a major and never will be — answer 'should I switch majors' by pointing at where it leads and what transfers.
Paramètres, retour & exemple (2)
Paramètresslug· string · requislocale· string · optionnel
Exemple d'appel{"name": "get_major", "arguments": {"slug": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - get_note≈ 82 tokens
The full text of one note, section by section, each section with the verified records it rests on. Use it when you need to quote or cite rather than summarise.
Paramètres, retour & exemple (2)
Paramètresslug· string · requislocale· string · optionnel
Exemple d'appel{"name": "get_note", "arguments": {"slug": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - get_occupation≈ 112 tokens
Full task-level assessment of one occupation. Every task carries direction, basis (evidenced vs inferred) and limits — what that judgement does NOT establish. The impact index is not a probability of job loss and never appears without its confidence and assessment date.
Paramètres, retour & exemple (2)
Paramètresslug· string · requislocale· string · optionnel
Exemple d'appel{"name": "get_occupation", "arguments": {"slug": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - get_ontology≈ 249 tokens
Where an occupation or a degree sits in the official classifications (U.S. Department of Labor O*NET 31.0; U.S. Department of Education CIP–SOC crosswalk; the EU's ESCO, the ILO's ISCO-08 and Singapore's SSOC 2024): the matching codes with how well each fits, the skills, knowledge and work activities O*NET rates highest (as O*NET's own importance words, no numbers), related occupations and which degrees lead to it; each of this site's tasks aligned to O*NET detailed work activities (or why none fits); and the rules this site's verified records read, with the verb that matters and whom it binds. For a degree: where the official crosswalk and this site's paths agree and disagree. Every block names its source. O*NET says what a job demands, not what automation is doing to it; never combine it with the impact index.
Paramètres, retour & exemple (2)
Paramètresslug· string · requislocale· string · optionnel
Exemple d'appel{"name": "get_ontology", "arguments": {"slug": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - get_role_tasks≈ 68 tokens
The task breakdown for one occupation. The unit of assessment is the task, never the job title.
Paramètres, retour & exemple (2)
Paramètresslug· string · requislocale· string · optionnel
Exemple d'appel{"name": "get_role_tasks", "arguments": {"slug": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - list_business_functions≈ 75 tokens
For the business side: the functions a company is organised into, and which occupations sit in each. Use this when someone describes a company rather than themselves.
Paramètres, retour & exemple (1)
Paramètreslocale· string · optionnel
Exemple d'appel{"name": "list_business_functions", "arguments": {"locale": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - query_ontology≈ 188 tokens
Walk the VOLO Ontology directly. No arguments: the object types and link types. `type`: the objects of that type. `type` + `id`: one object's properties and everything it links to, grouped by link. Add `link` (and `direction`: out|in) to follow one link. Types include Occupation, Task, TaskJudgement, Evidence, Regulation, WorkActivity and ClassificationConcept. Read-only; judgements keep their basis and limits, evidence its scope — carry them into the answer. No aggregate score exists.
Paramètres, retour & exemple (5)
Paramètresid· string · optionnellink· string · optionneltype· string · optionnellocale· string · optionneldirection· string · optionnel · out | in
Exemple d'appel{"name": "query_ontology", "arguments": {"id": "texte", "link": "texte", "type": "texte", "locale": "texte", "direction": "out"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - resolve_occupation_or_major≈ 265 tokens
Resolve a job title, a company's internal name for a role, a nickname or a degree name to a canonical VOLO entity. Call this FIRST whenever a person names their job. It matches names; it does not read sentences — so work out yourself which job the person means and pass only that title, in the singular ("taxi driver", not "Will robotaxis replace taxi drivers?"). Returns a match field of exact or approximate — when it is approximate, say which entity you read the question as. Null means this name did not match, not yet that VOLO lacks the job: before saying VOLO does not cover it, call describe_coverage and read its list of covered occupations and degrees — if one of them is what the person means (a synonym, a broader or narrower name), use that one and say which you chose. Only if none fits is it a gap in this site, which is not a statement about the job.
Paramètres, retour & exemple (2)
Paramètresquery· string · requislocale· string · optionnel
Exemple d'appel{"name": "resolve_occupation_or_major", "arguments": {"query": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - search≈ 74 tokens
Search occupations, majors and verified change records by keyword. Returns entries, not judgements.
Paramètres, retour & exemple (3)
Paramètreslimit· number · optionnelquery· string · requislocale· string · optionnel
Exemple d'appel{"name": "search", "arguments": {"query": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]}
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