Microsoft Dataverse skills for AI coding agents. Wraps the Dataverse MCP server, Dataverse CLI, Python SDK, and PAC CLI behind specialist skills for building, querying, deploying, and administering Dataverse environments.
Environment-level Dataverse administration — bulk delete, retention/archival, organization settings, OrgDB settings, recycle bin, audit, and the 37 allowlisted PPAC toggles. Use when the user wants to clean up data at scale, configure audit, change environment settings, manage retention policies, or list/cancel ERP…
One-step setup for a Dataverse environment — installs tools, authenticates, registers the MCP server, and writes .env. Use when starting a new project, switching environments, fixing authentication, or troubleshooting an MCP connection that won't come up.
Record-level CRUD and bulk operations — create, update, delete, upsert, CSV import, multi-table foreign-key loads, AI-generated sample data. Use when the user wants to write, modify, seed, or import data records into Dataverse tables.
Dataverse schema authoring and inspection — tables, columns, relationships, forms, and views. Use when the user wants to define, evolve, or inspect the data model — add a column, create a table, set up a lookup, customize a form, build a view, or list existing columns and relationships.
Foundational cross-cutting context for Dataverse / Power Platform work — scope and the skill map, the tool-capability reference, the safety rules, and the safe change lifecycle. Use when the user mentions Dataverse, Dynamics 365, Power Platform, CRM, or ERP; load this first for orientation. Specialist skills…
Bulk reads, multi-page iteration, and analytics over Dataverse data. Use when the user wants to read, list, filter, aggregate, group, join, or analyze records — including pandas DataFrame workflows and notebook exploration.
Security-role assignment, user access, application users, business units, and admin self-elevation in Dataverse environments. Use when the user wants to give someone access, grant a role, become an admin, or add a service principal.
Dataverse solution lifecycle — create, export, import, promote across environments, and validate deployments. Use when the user wants to package customizations, deploy to another environment, or move work between dev / test / prod.