JAJ Dataverse Dev MCP

io.github.jjohnsen由 GitHub 账号 jjohnsen 发布v0.1.4更新于 Oct 24, 2026

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

已验证STDIO仅桌面开发者工具商业与电商

概览

AI 生成的概览

本地 MCP 服务器,借助现有 Azure CLI 身份,让助手以轻量方式广泛访问多个 Power Platform 环境的 Dataverse Web API。

可以做什么
  • 通过 Web API 查询和更新 Dataverse 记录
  • 查看表、列、元数据、发布者和解决方案
  • 创建和配置非托管解决方案,并向其中添加现有组件
  • 调用 Dataverse 操作和函数
  • 导出解决方案以便部署到其他环境
  • 在 dev、test、prod 等命名环境间切换,并用 whoami 确认身份
适用场景
适合 Dataverse 和 Power Platform 开发者或顾问,希望让智能体直接检查、查询、修改或排查环境与解决方案,尤其是在多个项目、客户或租户之间切换时。
运行要求
通过 npx 以 stdio 在本地运行,需要 Node.js 20+。需安装并登录 Azure CLI(az login),并拥有一个或多个 Dataverse 环境 URL 的访问权限。环境在 environments.json 中定义,可用 DATAVERSE_ENVIRONMENTS_PATH 覆盖路径;每个环境可单独设置 tenantId。
安装前请注意
它以你的 Azure CLI 身份操作,并可写入 Dataverse:标记 allowWrite 为 true 的环境允许更新记录和更改解决方案,生产环境应保持只读。它是薄封装,提供较宽的 Web API 访问权限,而非受限的窄工具集。无需单独的应用注册或客户端密钥,但已登录的 Azure CLI 会话本身就是凭据。

安装

在 SourceWeft 中

  1. 打开 控制台中的 JAJ Dataverse Dev MCP,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

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.

来源:README.md,提交 2322769

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.1.4最新Sep 21, 2026

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