dv-connect Skill
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. Published by microsoft in Dataverse-skills.
Decision snapshot
Is this a fit?
Testing, Deployment, Writing, Includes SKILL.md
Compatibility not yet detected.
Permission behavior not yet detected.
Copy skill directory
2 months ago · MIT license
No specific cautions were detected. Review the source and requested permissions before installing.
What is dv-connect Skill?
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. Published by microsoft in Dataverse-skills. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Testing
- Deployment
- Writing
- Testing use cases
- Deployment use cases
Declared skill metadata
- Source file: .github/plugins/dataverse/skills/dv-connect/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use dv-connect Skill
- Use it for testing.
- Use it for deployment.
- Use it for writing.
Built with
Editorial notes
Source
- Creator: microsoft
- Repository: microsoft/Dataverse-skills
- Skill file: .github/plugins/dataverse/skills/dv-connect/SKILL.md
What it does
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.
Skill instructions
Skill: Connect One-step, idempotent Dataverse connection. Each step checks if it's already done and skips. Environment-First Rule — All metadata and plugin registrations are created in the environment via API/scripts, then pulled into the repo. Never hand-write solution XML to create components. Execute steps in order; do not skip ahead. Exception: Step 0 can short-circuit the flow if the workspace is already set up. Host entry test (FIRST — before Step 0). A local Windows/macOS host is capable by default, whichever agent drives it — it can run the CLIs, use persistent credentials, and host local MCP servers; an approval/sandbox gate isn't a constraint, and a missing CLI = install it. Constrained only when a runtime can't start, auth can't persist, or the host is explicitly ChatGPT Work Mode / Codex cloud / CI / no-keyring Linux (deterministic table: headless-hosts.md). Constrained → install only Python + pip deps, .env, scripts/auth.py, verify python scripts/auth.py --check, skip CLI
Verified compatibility and discovery
Frequently asked questions
What is dv-connect?
dv-connect is a open-source AI agent skill with Copy skill directory. One-step setup for a Dataverse environment — installs tools, authenticates, registers the MCP server, and writes .env.
Who is dv-connect best for?
dv-connect is best for reusing agent instructions, scripts, and references, testing workflows, deployment workflows, writing workflows.
How do I install dv-connect?
Install or run dv-connect using Copy skill directory. Check dv-connect for the latest setup command.
Is dv-connect actively maintained?
dv-connect may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
