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OI AI Adoption

com.operative-intelligence/ai-adoptionVersion 0.1.0

Advice on bringing AI into work processes, with sourced effects, risks and rules for SI, HR, DE, AT

Status

Responds86 msAnswered our handshake without sign-in.

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Last checked
Nov 14, 2026, 14:08 UTC
Latency
86 ms
Remotes responding
1 of 1
Sign-in
No sign-in
Hosting
EU hosting detected (detected, not a legal statement)
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://operative-intelligence.com/ai-adoptionResponds86 ms
No sign-in

Claude Code

claude mcp add --transport http ai-adoption https://operative-intelligence.com/ai-adoption

Claude Desktop and claude.ai

Settings > Connectors > Add custom connector
Name: ai-adoption
Remote MCP server URL: https://operative-intelligence.com/ai-adoption

Cursor

{
  "mcpServers": {
    "ai-adoption": {
      "url": "https://operative-intelligence.com/ai-adoption"
    }
  }
}

VS Code

code --add-mcp '{"name":"ai-adoption","type":"http","url":"https://operative-intelligence.com/ai-adoption"}'

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Tools

8 tools

Tools of OI AI Adoption
Read-only
Idempotent
Open world
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 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.NoYesYesNo
adoption_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 internal part answers questions such as what the advice is based on.NoYesYesNo
adoption_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.NoYesYesNo
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.NoYesYesNo
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.NoYesYesNo
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 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.NoYesYesNo
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.NoYesYesNo
plan_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.NoYesYesNo

Details

Registry status
Active
Published
Oct 15, 2026
Updated
Oct 15, 2026
Repository
Not given
Categories (suggested)
Knowledge and notesSuggested categories are assigned automatically from the registry text and may be wrong. Verified operators can correct them.
GDPR
Not declared

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