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OI AI Adoption
com.operative-intelligence/ai-adoption · v0.1.0
Measured by MCP Station
| Last check | Reachable |
|---|---|
| Checked at | — |
| Check success 7 / 30 days | — |
| First-try success 30 days | — |
| Median response | — |
| Lookups 30 days | — |
| Authentication | No auth |
| MCP version | 2025-06-18 |
| Rank score | — |
| Declared risk | Read-only (all tools declare readOnlyHint) |
| Capabilities declared | prompts, tools |
| Tool definitions | 8 tools · with description 100% · input schema is an object 100% · read/destructive hints 100% |
Description written by the publisher, not verified
Advice on bringing AI into work processes, with sourced effects, risks and rules for SI, HR, DE, AT
Connect
streamable-http · https://operative-intelligence.com/ai-adoption
claude mcp add --transport http ai-adoption https://operative-intelligence.com/ai-adoption{
"mcpServers": {
"ai-adoption": {
"url": "https://operative-intelligence.com/ai-adoption"
}
}
}Tools as reported by the server
get_readiness_questionsReturns 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.assess_ai_readinessScores 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.estimate_ai_costsEstimates 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 withplan_ai_rolloutReturns 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.adoption_list_process_typesReturns 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.adoption_find_patternsAdvises 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 toadoption_get_patternReturns 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 interadoption_get_regulationsReturns 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.
Website · JSON · Text for agents · Registry updated 2026-10-15