accueil / serveurs / Géo & Temps / com.operative-intelligence/ai-adoption
com.operative-intelligence/ai-adoption
serveur MCP (Model Context Protocol) · oi-ai-adoption-check 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 com.operative-intelligence/ai-adoption est sûr ?
Au dernier audit MCP Hub, le serveur MCP « com.operative-intelligence/ai-adoption » 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
- adoption_find_patterns≈ 2428 tokens
Advises on using AI in a process the user describes, from a curated knowledge base with sources. The caller passes the description, the task that best matches it and the process properties it states; the server selects deterministically and does not use a language model. The result puts questions to ask first (ask_first) at the top, then one recommended way as a workflow (recommendation: how it would work, what it brings with sourced effects only, what is needed, what to watch out for, a first step), at most two alternatives, and an internal part with ids, evidence levels and sources. For a general question without a concrete process, task general_question returns two business questions and no recommendation yet; with user_unsure true it returns simpler questions and example tasks.
Paramètres, retour & exemple (6)
Paramètreslang· string · optionnel · sl | en | de | hr
Language of the result: sl, en, de or hr. Texts not yet translated are returned in English and marked in the result.task· string · optionnel · general_question | voice_entry | data_entry_from_documents | mail_routing | register_checks | goods_receipt | customer_questions | email_reply_drafts
The task that best matches the description. One of: general_question: a general question without a concrete process (for example how to introduce AI in the business); voice_entry: Entering data into a form by voice instead of typing; data_entry_from_documents: Taking data from incoming documents (orders, invoices, delivery notes) into the ERP; mail_routing: Sorting incoming e-mail and documents to the right person or team; register_checks: Checking and completing customer and supplier data from official registers; goods_receipt: Receiving goods with a photo of the delivery note and weighing; customer_questions: Answering frequent customer questions; email_reply_drafts: Preparing replies to incoming e-mail; complete_requests: Collecting all the details of a request before it is handed over; quote_from_inquiry: Preparing a quote from a customer inquiry; lead_finding: Finding and qualifying potential customers; bookings_reminders: Online booking of appointments with reminders; summarise_documents: Summarising long documents into the points that matter; documents_from_templates: Creating documents such as quotes or reports from templates; compare_documents: Comparing documents and finding deviations; translate_documents: Translating technical documents; demand_forecast: Forecasting demand; shift_scheduling: Planning shifts while respecting rules and wishes; resource_scheduling: Scheduling vehicles, machines or rooms; stock_replenishment: Deciding how much stock to order; deal_margin: Seeing the margin of each deal or project; anomaly_detection: Catching duplicate invoices and unusual costs; purchasing_analysis: Analysing purchases and consumption; digital_checklists: Replacing paper checklists with digital ones (for example HACCP, vehicle checks); ai_compliance_check: Checking whether your use of AI complies with the rules; internal_document_search: Finding answers in internal instructions and policies; assistant_connected_to_systems: Letting the assistant you already pay for read your company systems; employee_onboarding: Onboarding new employees; professional_decision_support: Supporting professional decisions (clinical, technical)properties· object · optionnel
Process properties the description states; leave out what it does not saydescription· string · requis
The user's description of the process, unchangeduser_unsure· boolean · optionnel
Only for task general_question: true after the user said they do not know; returns simple questions and example tasksprocess_type· string · optionnel · data_capture | communication | documents | planning | control | knowledge
Optional filter by process type
Exemple d'appel{"name": "adoption_find_patterns", "arguments": {"description": "texte"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - adoption_get_pattern≈ 386 tokens
Returns the user-facing recommendation for one pattern (workflow, sourced effects, needs, risks, a first step) and, in an internal part, the full pattern with every claim resolved to its sources (title, publisher, URL, date read, location) and evidence level, or marked as having no source. The internal part answers questions such as what the advice is based on.
Paramètres, retour & exemple (3)
Paramètresid· string · requis · P01 | P02 | P03 | P04 | P05 | P06 | P07 | P08
Pattern id, e.g. P01lang· string · optionnel · sl | en | de | hr
Language of the result: sl, en, de or hr. Texts not yet translated are returned in English and marked in the result.sections· array · optionnel
Sections of the internal part to return; when left out: approaches, prerequisites, effect, risks, compliance
Exemple d'appel{"name": "adoption_get_pattern", "arguments": {"id": "P01"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - adoption_get_regulations≈ 304 tokens
Returns the EU and national provisions in the regulation register for the chosen country, optionally only those linked to one pattern, each with what it requires in plain words, the article, the date checked and a link to the official text.
Paramètres, retour & exemple (3)
Paramètreslang· string · optionnel · sl | en | de | hr
Language of the result: sl, en, de or hr. Texts not yet translated are returned in English and marked in the result.country· string · requis · SI | AT | DE | HR
Country: SI, AT, DE or HRpattern_id· string · optionnel · P01 | P02 | P03 | P04 | P05 | P06 | P07 | P08
Only provisions linked to this pattern
Exemple d'appel{"name": "adoption_get_regulations", "arguments": {"country": "SI"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - adoption_list_process_types≈ 179 tokens
Returns the six process types of the knowledge base (data capture, communication, documents, planning, control, knowledge) with a definition and the ids of the adoption patterns of each type.
Paramètres, retour & exemple (1)
Paramètreslang· string · optionnel · sl | en | de | hr
Language of the result: sl, en, de or hr. Texts not yet translated are returned in English and marked in the result.
Exemple d'appel{"name": "adoption_list_process_types", "arguments": {"lang": "sl"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - assess_ai_readiness≈ 260 tokens
Scores the answers from get_readiness_questions with fixed rules: a level from 0 to 4 per area, the rule behind each limit, the gaps found and a next step for each gap. Unanswered areas are reported as not assessed. The result is a self-assessment.
Paramètres, retour & exemple (2)
Paramètreslang· string · optionnel · sl | en | de | hr
Language of the result: sl, en, de or hr. Texts not yet translated are returned in English and marked in the result.answers· object · requis
Answers keyed by question id, each value an option id from get_readiness_questions
Exemple d'appel{"name": "assess_ai_readiness", "arguments": {"answers": {}}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - estimate_ai_costs≈ 1055 tokens
Estimates the costs of introducing AI, shown separately as external costs (contractor, DPIA, legal review, AI literacy training), internal staff time, licences per month and operations per month (hosting, model usage, maintenance), and the payback period in three savings scenarios. Public data with source and retrieval date: Eurostat labour costs (for internal staff time only), published licence, hosting and model price lists, the ECB exchange rate, and savings effects from four published studies. Amounts without a reliable public source are inputs; when they are missing, the result lists them and does not assume values. Also names, per country (SI, AT, DE, HR), where to check current public funding calls for digitalisation and AI; it gives no amounts and does not say whether any call is open.
Paramètres, retour & exemple (14)
Paramètreslang· string · optionnel · sl | en | de | hr
Language of the result: sl, en, de or hr. Texts not yet translated are returned in English and marked in the result.country· string · optionnel
ISO country code: SI, AT, DE or HR; otherwise the EU averagehosting· object · optionnellicence· object · optionnelexternal· object · optionneltask_type· string · optionnel · customer_support | professional_writing | knowledge_work | software_development
Type of work, to apply the effect measured in a published studycompliance· object · optionnelmodel_usage· object · optionnelinternal_hours· object · optionnelown_savings_share· number · optionnel
Own estimate of the share of process time saved; replaces the studyprocess_hours_per_week· number · requis
Hours per week currently spent on the processinternal_hourly_cost_eur· number · optionnelmaintenance_eur_per_month· number · optionnelinternal_it_hourly_cost_eur· number · optionnel
Exemple d'appel{"name": "estimate_ai_costs", "arguments": {"process_hours_per_week": 1}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - get_readiness_questions≈ 186 tokens
Returns the self-assessment questions on AI readiness in four areas (data, processes, people, compliance), each with its id, the reason it is asked and the allowed answer options. Answers are option ids, not free text.
Paramètres, retour & exemple (1)
Paramètreslang· string · optionnel · sl | en | de | hr
Language of the result: sl, en, de or hr. Texts not yet translated are returned in English and marked in the result.
Exemple d'appel{"name": "get_readiness_questions", "arguments": {"lang": "sl"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]} - plan_ai_rollout≈ 302 tokens
Returns a phased rollout plan (discovery, pilot, rollout, operations) with tasks, roles in RACI form, risks and indicators for the chosen implementation pattern. When readiness answers are given, preparation tasks for areas at level 0 or 1 are added to the discovery phase.
Paramètres, retour & exemple (3)
Paramètreslang· string · optionnel · sl | en | de | hr
Language of the result: sl, en, de or hr. Texts not yet translated are returned in English and marked in the result.answers· object · optionnel
Answers keyed by question id, each value an option id from get_readiness_questionspattern· string · requis · assistant_connector | workflow_automation | custom_application
Implementation pattern
Exemple d'appel{"name": "plan_ai_rollout", "arguments": {"pattern": "assistant_connector"}}Exemple de retour{"content": [{"type": "text", "text": "…"}]}
C'est votre serveur ?
Revendiquez-le sur l'espace créateur (preuve GitHub, domaine ou npm) pour afficher le badge « propriétaire vérifié » et lancer un pentest comportemental à la demande afin d'obtenir le badge « Vérifié ».