Dv Connect

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 / PAC / MCP. Capable → normal flow below.

Step 0: Detect existing setup (run this first)

Before touching anything, check whether this workspace is already connected to a Dataverse environment. Repeating setup on an already-configured workspace overwrites .env, re-registers MCP, and wastes time.

Gemini supports GA only. If Preview is requested, explain and stop before setup shortcuts.

Run these checks in order. If all four pass, skip straight to Step 7 (final verification) and stop there.

1. .env is present and complete — file exists at the workspace root and contains non-empty values for DATAVERSE_URL, TENANT_ID, and MCP_CLIENT_ID
2. MCP is registered — the host MCP list has a dataverse-* entry, or Gemini has its bundled dataverse entry, pointing at DATAVERSE_URL
3. Both auth surfaces match .env — dataverse auth who shows a profile whose Environment Url matches DATAVERSE_URL, AND pac org who against a PAC profile for the same URL succeeds. (DV CLI auth covers Connect / Data / Query / Metadata / MCP / Python; PAC auth covers dv-solution and dv-admin. Both are front-loaded at connect time so neither prompts later.)
4. Python SDK is importable and current — python -c "from PowerPlatform.Dataverse.client import DataverseClient; import pandas; from importlib.metadata import version; v=version('PowerPlatform-Dataverse-Client'); assert int(v.split('.')[0])>=1, f'SDK {v} is outdated, need >=1.0.0'" exits 0

If all pass: First ensure .env has valid attribution — set DATAVERSE_PLUGIN_VERSION to the loaded manifest version and add DATAVERSE_PLUGIN_AGENT (detected host, per Step 3) if absent or a stale unknown/placeholder. Confirm the detected setup (URL, profile, MCP server), and jump to Step 7. Do not otherwise rewrite .env, re-register MCP, or re-run pip install.

If any check fails: Proceed through the normal flow (Steps 1–7), but still use each step's own skip condition. A partially-configured workspace doesn't need a full redo — e.g., if only .env and MCP are missing but tools and auth are fine, start at Step 2 or Step 3.

Step 1: Ensure tools are installed

Check each tool independently -- report all missing tools at once. See tools-setup.md for install commands.

.NET SDK is needed for PAC CLI but NOT for the Dataverse CLI (the npm package bundles its own runtime). Node.js powers the Dataverse CLI npm package (@microsoft/dataverse), which is used as the MCP proxy and for scripted data plane actions. Azure CLI is used as a fallback for environment discovery when PAC CLI isn't available (see mcp-configuration.md Step 3b). GitHub CLI is not needed for connecting — it's used later for ALM/CI/CD scenarios (see dv-solution).

If any tool is missing, install it (see tools-setup.md), then verify. If winget installs a tool but it's not in PATH, ask the user to restart the terminal.

After Python is confirmed, check if deps are already present before installing:

python -c "from PowerPlatform.Dataverse.client import DataverseClient; import azure.identity, msal, msal_extensions, requests, pandas; print('OK')"

If it prints OK, skip pip. Otherwise:

pip install --upgrade azure-identity requests PowerPlatform-Dataverse-Client pandas msal msal-extensions

msal + msal-extensions let scripts/auth.py reuse the dataverse auth create cache -- one sign-in for CLI, MCP, Python.

After Node.js is confirmed, install the Dataverse CLI only if missing (do not re-run on every connect -- on managed devices each @latest fetch can trigger npm-registry security prompts; see tools-setup.md):

npm install -g @microsoft/dataverse@latest

Skip condition: All tools present, Python SDK installed, and pandas importable (python -c "import pandas").

Step 2: Discover and select the environment

Before asking the user for a URL, check what's already available.

Auth tool choice. Two tools, two AAD apps, two caches — front-load both at connect:

1. dataverse auth create (app 0c412cc3-…) covers DV CLI + MCP + Python.
2. pac auth create (PAC's own app) covers dv-solution + dv-admin.

Check for an existing DV CLI profile first, then fall back to PAC for environment discovery if needed:

dataverse auth list
dataverse auth who
pac auth list   # PAC profiles are still useful for env discovery / pac org list

If dataverse auth who shows a profile and its environment matches the user's target:

• Reuse it. Set DATAVERSE_URL and TENANT_ID from the profile.

If no DV CLI profile exists (or it points at the wrong environment):

• Ask: "Do you want to connect to an existing environment or create a new one?"

Before selecting, check for tenant/region mismatch. If the target URL uses a different region than the authenticated account's environments, create a new profile for the correct tenant rather than reuse the old one:

dataverse auth create --environment <url>          # interactive (WAM broker on Windows → no browser tab)
dataverse auth create --environment <url> --deviceCode   # headless / remote / SSH

If the user hits an admin-consent error, the CLI prints the correct scope-scoped consent URL to share with a tenant admin — do not synthesize one.

To switch between existing DV CLI profiles:

dataverse auth select --name <profile-name>

To create a new environment (requires admin permissions):

pac admin create --name "<name>" --type "<type>" --region "<region>"

If this fails with permissions error, guide the user to Power Platform Admin Center to create it, then connect.

Confirm connection:

dataverse auth who
dataverse org who --context "app=dataverse-skills/<ver>;skill=dv-connect;agent=<agent>"

Parse the output to extract DATAVERSE_URL, TENANT_ID, and — on ERP-linked envs — ERP_URL (see erp-detection.md).

If neither command shows a tenant ID, fall back to:

curl -sI https://<org>.crm.dynamics.com/api/data/v9.2/ \
  | grep -i "WWW-Authenticate" \
  | sed -n 's|.*login\.microsoftonline\.com/\([^/]*\).*|\1|p'

Step 2b: Front-load PAC CLI auth for the same environment

PAC uses its own AAD app, so a separate sign-in is required for dv-solution and dv-admin — do it now.

pac auth list                                       # skip if a profile for $DATAVERSE_URL exists
pac auth create --name <orgid> --environment <DATAVERSE_URL>

Use the same account as Step 2. If PAC CLI is not installed, skip with a note that dv-solution / dv-admin will need it later.

Step 3: Create .env

Present authentication options:

How would you like to authenticate with Dataverse?

1. Interactive login (recommended) — Sign in via browser. No app registration needed. Token stays cached across sessions.
2. CI/CD service principal — Use CLIENT_SECRET or CLIENT_CERTIFICATE_PATH.

Write .env directly — do not instruct the user to create it:

Use one detected tool_type to derive both MCP_CLIENT_ID and canonical attribution. Set PLUGIN_VERSION from the loaded manifest; Antigravity uses .claude-plugin/plugin.json because native plugin.json has none.

tool_type = "<copilot | claude | cursor | codex | gemini | antigravity | unknown>"
plugin_version = "<plugin manifest version, e.g. 1.5.0>"
mcp_client_id = "aebc6443-996d-45c2-90f0-388ff96faa56" if tool_type == "copilot" else "0c412cc3-0dd6-449b-987f-05b053db9457"
agent_host = {
    "copilot": "copilot", "claude": "claude-code", "cursor": "cursor",
    "codex": "codex", "gemini": "gemini-cli",
    "antigravity": "antigravity-cli",
}.get(tool_type, "unknown")

with open(".env", "w") as f:
    f.write(f"DATAVERSE_URL={dataverse_url}\n")
    f.write(f"TENANT_ID={tenant_id}\n")
    f.write(f"MCP_CLIENT_ID={mcp_client_id}\n")
    f.write(f"DATAVERSE_PLUGIN_VERSION={plugin_version}\n")
    f.write(f"DATAVERSE_PLUGIN_AGENT={agent_host}\n")
    f.write(f"SOLUTION_NAME={solution_name}\n")
    f.write(f"PUBLISHER_PREFIX=\n")  # filled in when solution is created
    f.write(f"PAC_AUTH_PROFILE=nonprod\n")
    if client_id:
        f.write(f"CLIENT_ID={client_id}\n")
    if client_secret:
        f.write(f"CLIENT_SECRET={client_secret}\n")

Ensure .env is in .gitignore:

import os

GITIGNORE_ENTRIES = [
    ".env", ".vscode/settings.json", ".claude/mcp_settings.json",
    ".token_cache.bin", ".dataverse/", "*.snk", "__pycache__/", "*.pyc",
    "solutions/*.zip", "plugins/**/bin/", "plugins/**/obj/",
]
gitignore = open(".gitignore").read() if os.path.exists(".gitignore") else ""
missing = [e for e in GITIGNORE_ENTRIES if e not in gitignore]
if missing:
    with open(".gitignore", "a") as f:
        f.write("\n" + "\n".join(missing) + "\n")

Skip condition: .env already exists with all required values.

Step 4: Set up project structure (new projects only)

If this is a new project (no scripts/ directory):

mkdir -p solutions plugins scripts

Ensure scripts/auth.py and scripts/enable-mcp-client.py exist -- see references/helper-scripts.md.

Copy templates/CLAUDE.md to the repo root if it doesn't exist. Replace placeholders ({{DATAVERSE_URL}}, {{SOLUTION_NAME}}, {{PUBLISHER_PREFIX}}) with values from .env.

Step 5: Verify the connection

dataverse auth who
pac org who
python scripts/auth.py --check

--check makes a real data-plane call (not just a token) — the only proof the org is actually reachable; a token can be minted while the org domain is blocked. All must resolve the same user/environment, proving the DV CLI cache, the PAC profile (Step 2b), and Python's reuse of the shared cache are wired.

If any fail:

• dataverse auth who fails → re-run Step 2.
• pac org who fails → re-run Step 2b.
• python scripts/auth.py --check prints a device-code URL → browser/WAM cache has no Python-reusable token. Auto-fix: re-run dataverse auth create --environment <url> --deviceCode, then retry. If it still prompts, check pip show msal msal-extensions. Headless hosts (ChatGPT / Codex cloud / CI): dataverse auth create can't persist here — don't loop (see headless-hosts.md).
• python scripts/auth.py --check prints NOT REACHABLE with a connection/timeout error → the org domain is blocked by network egress, not auth. Do NOT report success or a count — see headless-hosts.md remediation.
• Other Python error → check SDK install and .env.

Before metadata work, also confirm the account has the prvCreateEntity customization privilege — see tools-setup.md.