JAJ Dataverse Dev MCP

io.github.jjohnsen由 GitHub 帳號 jjohnsen 發布v0.1.4更新於 Oct 24, 2026

Xrm/Power Platform/Dataverse MCP for devs, Azure CLI auth, Web API and multi-environment support

已驗證STDIO僅桌面開發者工具商業與電商

概覽

AI 產生的概覽

本機 MCP 伺服器,透過現有的 Azure CLI 身分,讓助理以輕量方式廣泛存取多個 Power Platform 環境的 Dataverse Web API。

可以做什麼
  • 透過 Web API 查詢與更新 Dataverse 記錄
  • 檢視資料表、欄位、中繼資料、發行者與解決方案
  • 建立與設定非受控解決方案,並將現有元件加入其中
  • 呼叫 Dataverse 動作與函式
  • 匯出解決方案以便部署到其他環境
  • 在 dev、test、prod 等具名環境間切換,並用 whoami 確認身分
適用情境
適合 Dataverse 與 Power Platform 開發人員或顧問,希望讓代理直接檢視、查詢、修改或排查環境與解決方案,尤其是在多個專案、客戶或租用戶之間切換時。
執行需求
透過 npx 以 stdio 在本機執行,需要 Node.js 20+。需安裝並登入 Azure CLI(az login),並具備一個或多個 Dataverse 環境 URL 的存取權。環境定義於 environments.json,可用 DATAVERSE_ENVIRONMENTS_PATH 覆寫路徑;每個環境可個別設定 tenantId。
安裝前請注意
它以你的 Azure CLI 身分運作,並可寫入 Dataverse:標記 allowWrite 為 true 的環境允許更新記錄與變更解決方案,正式環境應保持唯讀。它是薄封裝,提供較廣的 Web API 存取,而非受限的窄工具集。不需另外的應用程式註冊或用戶端密碼,但已登入的 Azure CLI 工作階段本身就是憑證。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 JAJ Dataverse Dev MCP,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

JAJ Dataverse Dev MCP

Lightweight MCP server for day-to-day Dataverse and Power Platform development.

Connect your agents to multiple Dataverse environments using your existing Azure CLI identity. The server exposes a thin, agent-friendly layer over the Web API for data, metadata, solutions, components, troubleshooting, and development tasks.

Agent → MCP → Azure CLI identity → Dataverse Web API

Quick Start for VS Code + GitHub Copilot

Add the server to .vscode/mcp.json:

json
{  "servers": {		"dataverse-dev": {			"command": "npx",			"args": [ "-y", "jaj-dataverse-dev-mcp" ]		}	}}

Save the file and press Start. The first start may take some time while npx downloads the package.

Sign in with Azure CLI:

bash
az login

Create environments.json in your project root with the environments you need:

json
{  "environments": {    "dev": {      "url": "https://org8ffb6d07.crm.dynamics.com/",      "allowWrite": true    }  }}

Open Copilot and try:

  • List the available Dataverse environments
  • Call whoami for the dev environment
  • Show me the names and IDs of the five most recently created accounts
  • List the unmanaged solutions

That's it!

Other MCP-compatible agents follow the same pattern: run jaj-dataverse-dev-mcp over stdio and provide access to your local Azure CLI session and connection configuration.

Quick Start for Claude Desktop

Add the server to claude_desktop_config.json:

  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
json
{  "mcpServers": {    "dataverse-dev": {      "command": "npx",      "args": ["-y", "jaj-dataverse-dev-mcp"],      "env": { "DATAVERSE_ENVIRONMENTS_PATH": "C:/Users/you/project/environments.json" }    }  }}

Save the file and fully quit and restart Claude Desktop (config changes aren't picked up by simply closing the window).

Continue from "Sign in with Azure CLI..." in Quick Start for VS Code + GitHub Copilot

Why this project?

There are already several Dataverse MCP implementations, including Microsoft's own tooling.

This project grew out of day-to-day development work where agents frequently needed capabilities beyond the available specialized tools. In many cases, the agent could solve the task successfully by constructing Dataverse Web API requests directly.

This MCP embraces that approach.

Instead of hiding Dataverse behind a large abstraction, it provides broad access to the Web API through a thin wrapper.

It is also designed for developers and consultants who regularly move between projects, customers, and Dataverse environments.

One MCP server can work with multiple Dataverse environments while using existing Azure CLI identity. No separate app registration, client ID, or client secret is required.

Prerequisites

  • Node.js 20+
  • Azure CLI installed and signed in
  • Access to one or more Dataverse environment URLs

Authentication

# Authentication is based on your current Azure CLI identity:
az login
# Useful variants:
az login --tenant <tenant-id>       # Specific tenant, if your tenant is not the defaultaz login --allow-no-subscriptions   # Tenant without subscriptionsaz login --use-device-code          # Remote/headless environments
# To inspect the currently active Azure CLI account:
az account show

Dataverse environments

Environments are configured in environments.json in the project root and identified by friendly names such as dev, test, prod.
Agents use these names when selecting which Dataverse environment to work with.

If an environment is in a different tenant than the default Azure CLI tenant, add a tenantId for that environment.

DATAVERSE_ENVIRONMENTS_PATH can be used to override the config file path at runtime.

Example:

json
{  "environments": {    "dev": {      "url": "https://YOUR-DEV.crm.dynamics.com/",      "allowWrite": true    },    "test": {      "url": "https://YOUR-TEST.crm4.dynamics.com",      "allowWrite": false    },    "prod": {      "url": "https://YOUR-PROD.crm4.dynamics.com",      "allowWrite": false,      "tenantId": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"    }  }}

Add project-specific Copilot instructions

For better agent behavior, add Dataverse-specific instructions to the project where you use the MCP.

Copy docs/examples/copilot-instructions.md to .github/copilot-instructions.md in the workspace where you use the MCP server, then customize it for your project:

  • replace YOUR-dev, YOUR-test, and YOUR-prod with the environment names from environments.json
  • replace YOUR_DEFAULT_SOLUTION with the unique name of the primary Dataverse solution
  • adjust the default environment and safety rules for the project

Commit the customized file to the project repository so all contributors use the same guidance.

Run directly with npx

The package can also be launched manually with stdio as default transport:

npx -y jaj-dataverse-dev-mcp

For development or clients that use Streamable HTTP add --http.

What can it be used for?

Although the MCP is intentionally a thin wrapper around the Dataverse Web API, it can support a broad range of development and troubleshooting tasks, for example:

  • query and update Dataverse records
  • inspect tables, columns, metadata, publishers, and solutions
  • create and configure unmanaged solutions
  • add existing components to solutions
  • work with Dataverse actions and functions
  • export solutions for deployment to other environments

This makes it useful for both direct development tasks and agent-driven workflows where the agent inspects Dataverse, decides on the next action, and performs it through the MCP.

來源:README.md,提交 2322769

工具

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SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

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  1. v0.1.4最新Sep 21, 2026

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