The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Jaj Dataverse Dev MCP listing page.
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
Add the server to .vscode/mcp.json:
Save the file and press Start. The first start may take some time while npx downloads the package.
Sign in with Azure CLI:
Create environments.json in your project root with the environments you need:
Open Copilot and try:
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.
Add the server to claude_desktop_config.json:
%APPDATA%\Claude\claude_desktop_config.json~/Library/Application Support/Claude/claude_desktop_config.jsonSave 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
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.
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:
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:
YOUR-dev, YOUR-test, and YOUR-prod with the environment names from environments.jsonYOUR_DEFAULT_SOLUTION with the unique name of the primary Dataverse solutionCommit the customized file to the project repository so all contributors use the same guidance.
The package can also be launched manually with stdio as default transport:
For development or clients that use Streamable HTTP add --http.
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:
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.