---
name: Dataverse Connect
slug: dataverse-connect
category: DevOps
description: Dataverse Connect sets up a Dataverse workspace by installing tools, authenticating, registering the MCP server, and writing .env. Use it when starting a new project, switching environments, or fixing a broken connection.
github: "https://github.com/microsoft/Dataverse-skills/tree/main/.github/plugins/dataverse/skills/dv-connect"
stars: 216
forks: 57
install: "npx degit https://github.com/microsoft/Dataverse-skills/tree/main/.github/plugins/dataverse/skills/dv-connect ~/.claude/skills/dv-connect"
installs_to: ~/.claude/skills/dv-connect
source_path: .github/plugins/dataverse/skills/dv-connect/SKILL.md
collection_size: 9
category_size: 920
collection_url: "https://dirskills.com/collections/microsoft/Dataverse-skills"
added: 2026-09-04T05:25:38.080Z
last_synced: 2026-09-04T05:25:38.080Z
canonical_url: "https://dirskills.com/skills/dataverse-connect"
---

# Dataverse Connect

Dataverse Connect sets up a Dataverse workspace by installing tools, authenticating, registering the MCP server, and writing .env. Use it when starting a new project, switching environments, or fixing a broken connection.

**Install:**

```bash
npx degit https://github.com/microsoft/Dataverse-skills/tree/main/.github/plugins/dataverse/skills/dv-connect ~/.claude/skills/dv-connect
```

## README

# 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](references/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.

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** — `.mcp.json` (Claude Code) or the equivalent Copilot / Cursor config file has a `dataverse-*` server entry pointing at the `DATAVERSE_URL` from `.env`
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:** Refresh `DATAVERSE_PLUGIN_VERSION` in `.env` if it's stale, 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](references/tools-setup.md) for install commands.

| Tool | Check |
|---|---|
| Python 3 | `python --version` |
| Git | `git --version` |
| Node.js | `node --version` |
| PAC CLI | `pac` (prints version banner; `pac --version` is not valid) (see [tools-setup.md](references/tools-setup.md) if not in PATH) |
| Dataverse CLI | `npm list -g @microsoft/dataverse` |
| .NET SDK | `dotnet --version` |
| Azure CLI | `az --version` |

.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](references/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](references/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](references/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](https://admin.powerplatform.microsoft.com/) to create it, then connect.

**Confirm connection:**
```
dataverse auth who
dataverse org who      # or: pac org who
```
Parse the output to extract `DATAVERSE_URL`, `TENANT_ID`, and — on ERP-linked envs — `ERP_URL` (see [`erp-detection.md`](references/erp-detection.md)).

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

Detect the current tool (Claude or Copilot) from context and set `MCP_CLIENT_ID` automatically:
- Claude (CLI or VSCode extension): `0c412cc3-0dd6-449b-987f-05b053db9457`
- GitHub Copilot: `aebc6443-996d-45c2-90f0-388ff96faa56`

Also set plugin attribution variables for User-Agent tagging. **Fill in the two literals below from your own context** — you (the agent) loaded this plugin, so you already know both values:

- `PLUGIN_VERSION` — the `version` field of your loaded plugin manifest (e.g. `"1.5.0"`). At runtime, `auth.py` re-reads this from the live manifest via host env vars; this `.env` entry is a fallback for offline cases.
- `AGENT` — your host identity, one of: `claude-code`, `copilot`, `cursor`, `codex`, or `unknown`. Must match an entry in `_ALLOWED_AGENTS` in `auth.py` — if you don't recognize your host, use `unknown`.

```python
# Substitute these two literals from your loaded plugin context.
# Do NOT leave the angle-bracket placeholders — replace with real values.
plugin_version = "<plugin manifest version, e.g. 1.5.0>"
agent_host = "<your host name: claude-code | copilot | cursor | codex | 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`:

```python
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
```

Copy plugin scripts:
```
cp .github/plugins/dataverse/scripts/auth.py scripts/
```

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`.

**Skip condition:** `scripts/auth.py` exists.

---

## 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](references/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](references/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](references/tools-setup.md#privilege-preflight).

---

## Step 6: Configure MCP server

**Skip this step** if MCP is already configured:
- `.mcp.json` or `~/.copilot/mcp-config.json` or `~/.cursor/mcp.json` or `~/.codex/config.toml` contains a Dataverse server entry
- `claude mcp list` shows a `dataverse-*` server registered

If MCP is not configured, follow [mcp-configuration.md](references/mcp-configuration.md):

1. Detect which tool the user is running (Copilot, Claude, Cursor, or Codex) from context
2. Set `MCP_CLIENT_ID` based on tool choice
3. Get environment URL from `.env`
4. Default to GA endpoint (`/api/mcp`)
5. Register the MCP server per host (see the per-host blocks below)
6. Handle admin consent and allowlist — prefer `dataverse mcp allow <MCP_CLIENT_ID>` over the portal (one-time per tenant/environment)

**Plugin attribution for MCP:** This plugin uses the **stdio proxy** transport (`npx @microsoft/dataverse mcp <url>`). When registering it, include `DATAVERSE_OPERATION_CONTEXT` in the env block so the CLI appends it to its User-Agent on requests to `/api/mcp`. Build the value from `.env`:

```
DATAVERSE_OPERATION_CONTEXT=app=dataverse-skills/{DATAVERSE_PLUGIN_VERSION};skill=mcp-direct;agent={DATAVERSE_PLUGIN_AGENT}
```

For Claude Code (`claude mcp add -t stdio`), pass it via `-e DATAVERSE_OPERATION_CONTEXT=...`. For Copilot/Cursor JSON configs, add it to the `"env"` object in the stdio server entry; for Codex, add it to its `[mcp_servers.<name>.env]` table.

**Important:** MCP configuration requires an editor/CLI restart.

**For Copilot:** Write the JSON config, then:
> ✅ Dataverse MCP server configured. **Restart your editor** for changes to take effect.

**For Claude:** Run the `claude mcp add` command, then warn the user about the auth popup that will appear on next launch:
> ✅ Dataverse MCP server registered. Restart Claude Code to enable MCP tools.
> Remember to **use `claude --continue` to resume the session** without losing context.
>
> On restart, a browser window may open to sign in to your Dataverse environment (the MCP proxy authenticating on your behalf). See [mcp-configuration.md](references/mcp-configuration.md) for details.

**For Cursor:** Write the JSON config, then:
> ✅ Dataverse MCP server `dataverse-{orgid}` configured in `~/.cursor/mcp.json`. **Reload the Cursor window** (Ctrl+Shift+P → "Developer: Reload Window") for the new MCP server to appear under Settings → Tools & MCPs.
>
> On first use the `npx @microsoft/dataverse` proxy signs in via browser device code, then reuses the shared cache silently. See [mcp-configuration.md](references/mcp-configuration.md).

**For Codex:** Write the TOML config to `~/.codex/config.toml`. Codex loads MCP tools only at startup, so don't claim they're callable until the user restarts. Tell the user:
> ✅ Dataverse MCP server `dataverse-{orgid}` configured in `~/.codex/config.toml`. **Restart Codex** (CLI) or reload the Codex IDE to load the MCP tools.

---

## Step 7: Final verification

After the editor/CLI restarts, **both** of these must succeed before declaring the setup complete:

**Check 1: `claude mcp list` (or Copilot equivalent) shows ✓ Connected**
```
claude mcp list
```
This proves the MCP server process starts and speaks the MCP protocol. It does NOT by itself prove that data operations work — authentication, environment allowlisting, and endpoint reachability are only exercised on the first real tool call.

**Check 2: Agent successfully lists tables via `describe`/`search` and returns data**
> "List the tables in my Dataverse environment."

This proves end-to-end wiring: auth, tenant consent, environment allowlist, and endpoint reachability are all correct. If the agent falls back to PAC CLI or Web API, see [mcp-configuration.md](references/mcp-configuration.md) troubleshooting.

Only when **both** checks pass is the setup verified.

**Interpreting failures:**

- If Check 1 fails (server not ✓ Connected): the MCP server itself cannot start. Re-run Step 6 and check that `npx`/Node.js are installed and the MCP registration succeeded.
- If Check 1 passes but Check 2 fails (server starts but `describe`/`search` errors): the server can speak MCP but cannot reach or read Dataverse. Run `--validate` below to diagnose.

**Diagnostic — `--validate` (for failure investigation only):**
```
npx @microsoft/dataverse mcp {DATAVERSE_URL} --validate
```
This exercises two Dataverse MCP endpoints with a fresh authentication handshake and reports detailed errors (auth, allowlist, consent, endpoint reachability):

- **GA / Production endpoint** — `{DATAVERSE_URL}/api/mcp`. This is the one the plugin actually uses at runtime.
- **Preview endpoint** — `{DATAVERSE_URL}/api/mcp_preview`. Opt-in per environment; not used by the plugin.

**Do not use `--validate` as a success gate on first-time setup.** On a freshly configured workspace, the token cache hasn't warmed up, so `--validate` can fail with `MsalClientException` or `403` while MCP is actually working fine on subsequent real calls. Reserve `--validate` for diagnosing a confirmed failure in Check 1 or Check 2.

**How to read `--validate` output:**

- **Look at the GA / Production endpoint (`/api/mcp`) result first.** If this passes, MCP will work for normal plugin usage regardless of what the Preview endpoint reports.
- **A `403 Forbidden` on the Preview endpoint (`/api/mcp_preview`) is expected for most environments.** Preview is opt-in per environment; if your environment hasn't enabled it, the Preview check will always fail. This does not indicate a broken setup.
- **Ignore the overall exit code and the `⚠ Partial success` warning in this case.** The validator returns exit code `1` (failure) unless BOTH `/api/mcp` and `/api/mcp_preview` pass. Because most environments don't enable the Preview endpoint, `--validate` will exit `1` even when MCP is fully functional via the GA endpoint. Focus on per-endpoint results, not the aggregate status.
- **If the GA endpoint (`/api/mcp`) fails:** that's the real signal to investigate — auth, tenant consent, environment allowlist, or endpoint reachability.

### MCP Server Capabilities

For what MCP can and can't do (data CRUD + batch up to 25, table/column creation incl. choice/lookup, `search`/`describe`, file upload/download) versus the SDK / Web API, see the **overview** skill's Tool Capabilities matrix.

After verifying MCP works, tell the user:

> ✅ Connected to Dataverse at `{DATAVERSE_URL}`. Tools installed, authenticated, MCP live.
>
> You can now:
> - Create tables, columns, and relationships (`dv-metadata`)
> - Write and import data (`dv-data`)
> - Query and analyze data (`dv-query`)
> - Export and promote solutions (`dv-solution`)
>
> To create your first solution, see the `dv-solution` skill.
> To load sample data (accounts, contacts, opportunities), ask: "Load demo data into my Dataverse environment."

---

## Supported Agents

This plugin's skill files are natively loaded by both **GitHub Copilot CLI** and **Claude Code CLI** when installed as a plugin. No manual context-loading is needed — both agents discover and invoke skills automatically.

The PAC CLI commands, Python scripts, and XML templates work identically in both environments.