JAJ Dataverse Dev MCP

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

• 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 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.