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JAJ Dataverse Dev MCP

by jjohnsenversion 0.1.4i★ –iRuns on your computer
Registry nameio.github.jjohnsen/jaj-dataverse-dev-mcp

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Developer tools

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: DATAVERSE_ENVIRONMENTS_PATH

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "jaj-dataverse-dev": {
      "command": "npx",
      "args": [
        "-y",
        "jaj-dataverse-dev-mcp"
      ],
      "env": {
        "DATAVERSE_ENVIRONMENTS_PATH": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add jaj-dataverse-dev --env DATAVERSE_ENVIRONMENTS_PATH=your-value -- npx -y jaj-dataverse-dev-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "jaj-dataverse-dev": {
      "command": "npx",
      "args": [
        "-y",
        "jaj-dataverse-dev-mcp"
      ],
      "env": {
        "DATAVERSE_ENVIRONMENTS_PATH": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "jaj-dataverse-dev": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "jaj-dataverse-dev-mcp"
      ],
      "env": {
        "DATAVERSE_ENVIRONMENTS_PATH": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • DATAVERSE_ENVIRONMENTS_PATH env
    Optional path to the Dataverse environments configuration file. Defaults to ./environments.json.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account jjohnsen, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

  • More stars than 0% of the other 1391 servers in this category
  • Published to the registry more recently than 55% of the other 1391 servers in this category
  • Basic checks equal to or better than 100% of the other 1391 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is JAJ Dataverse Dev MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.4) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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:

{

"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:

az login

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

{

"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
{

"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

Authentication

# Authentication is based on your current Azure CLI identity:

az login

Useful variants:

az login --tenant # Specific tenant, if your tenant is not the default az login --allow-no-subscriptions # Tenant without subscriptions az 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:

{

"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.

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