Azure Data Explorer MCP Server

A [Model Context Protocol][mcp] (MCP) server for Azure Data Explorer/Eventhouse in Microsoft Fabric.

This provides access to your Azure Data Explorer/Eventhouse clusters and databases through standardized MCP interfaces, allowing AI assistants to execute KQL queries and explore your data.

Features

Execute KQL queries against Azure Data Explorer

Discover and explore database resources

Authentication support

Docker containerization support

Provide interactive tools for AI assistants

The list of tools is configurable, so you can choose which tools you want to make available to the MCP client. This is useful if you don't use certain functionality or if you don't want to take up too much of the context window.

Usage

Configure the environment variables for your ADX cluster, either through a .env file or system environment variables:

Add the server configuration to your client configuration file. For example, for Claude Desktop:

Note: if you see Error: spawn uv ENOENT in Claude Desktop, you may need to specify the full path to uv or set the environment variable NO_UV=1 in the configuration.

Docker Usage

This project includes Docker support for easy deployment and isolation.

Building the Docker Image

Build the Docker image using:

Running with Docker

You can run the server using Docker in several ways:

Using docker run directly:

Using docker-compose:

Create a .env file with your Azure Data Explorer credentials and then run:

Running with Docker in Claude Desktop

To use the containerized server with Claude Desktop, update the configuration to use Docker with the environment variables:

This configuration passes the environment variables from Claude Desktop to the Docker container by using the -e flag with just the variable name, and providing the actual values in the env object.

Using as a Dev Container / GitHub Codespace

This repository can also be used as a development container for a seamless development experience. The dev container setup is located in the devcontainer-feature/adx-mcp-server folder.

For more details, check the devcontainer README.

Development

Contributions are welcome! Please open an issue or submit a pull request if you have any suggestions or improvements.

This project uses `uv` to manage dependencies. Install uv following the instructions for your platform:

You can then create a virtual environment and install the dependencies with:

Project Structure

The project has been organized with a src directory structure:

Testing

The project includes a comprehensive test suite that ensures functionality and helps prevent regressions.

Run the tests with pytest:

Tests are organized into:

Configuration validation tests

Server functionality tests

Error handling tests

Main application tests

When adding new features, please also add corresponding tests.

Tools

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License

MIT