What can you do with this server?

The **adx-mcp-server** is an MCP server that connects to Azure Data Explorer/Eventhouse databases, enabling AI assistants to interact with data through standardized interfaces. Key capabilities: * **Execute KQL queries** against configured databases * **Discover and explore database resources**: * List available tables with names and associations * View table schemas, including column names and data types * Sample data from tables with customizable sample sizes * **Authentication support** including token credentials and Workload Identity for AKS * **Deployment options** through Docker containerization and Dev Container/GitHub Codespace compatibility

Which integrations are available for this server?

Used for loading environment variables from a [.env](/mcp/servers/integrations/dotenv) file for configuration of the Azure Data Explorer connection details and authentication credentials. Supports comprehensive testing of the MCP server functionality, including configuration validation, server operation, and error handling tests.

Azure Data Explorer MCP Server

codecov License: MIT Python 3.12

A (MCP) server that enables AI assistants to execute KQL queries and explore Azure Data Explorer (ADX/Kusto) databases through standardized interfaces.

This server provides seamless access to Azure Data Explorer and Eventhouse (in Microsoft Fabric) clusters, allowing AI assistants to query and analyze your data using the powerful Kusto Query Language.

Features

Query Execution

Execute KQL queries - Run arbitrary KQL queries against your ADX database
Structured results - Get results formatted as JSON for easy consumption

Database Discovery

List tables - Discover all tables in your database
View schemas - Inspect table schemas and column types
Sample data - Preview table contents with configurable sample sizes
Table statistics - Get detailed metadata including row counts and storage size

Authentication

DefaultAzureCredential - Supports Azure CLI, Managed Identity, and more
Workload Identity - Native support for AKS workload identity
Flexible credentials - Works with multiple Azure authentication methods

Deployment Options

Multiple transports - stdio (default), HTTP, and Server-Sent Events (SSE)
Docker support - Production-ready container images with security best practices
Dev Container - Seamless development experience with GitHub Codespaces

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.

Related MCP server: Metabase MCP Server

Usage

Login to your Azure account which has the permission to the ADX cluster using Azure CLI.
Configure the environment variables for your ADX cluster, either through a .env file or system environment variables:

# Required: Azure Data Explorer configuration ADX_CLUSTER_URL=https://yourcluster.region.kusto.windows.net ADX_DATABASE=your_database # Optional: Azure Workload Identity credentials # AZURE_TENANT_ID=your-tenant-id # AZURE_CLIENT_ID=your-client-id # ADX_TOKEN_FILE_PATH=/var/run/secrets/azure/tokens/azure-identity-token # Optional: Custom MCP Server configuration ADX_MCP_SERVER_TRANSPORT=stdio # Choose between http/sse/stdio, default = stdio # Optional: Only relevant for non-stdio transports ADX_MCP_BIND_HOST=127.0.0.1 # default = 127.0.0.1 ADX_MCP_BIND_PORT=8080 # default = 8080

Azure Workload Identity Support

The server now uses WorkloadIdentityCredential by default when running in Azure Kubernetes Service (AKS) environments with workload identity configured. It prioritizes the use of WorkloadIdentityCredential whenever the necessary environment variables are present.

For AKS with Azure Workload Identity, you only need to:

Make sure the pod has AZURE_TENANT_ID and AZURE_CLIENT_ID environment variables set
Ensure the token file is mounted at the default path or specify a custom path with ADX_TOKEN_FILE_PATH

If these environment variables are not present, the server will automatically fall back to DefaultAzureCredential, which tries multiple authentication methods in sequence.

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

{ "mcpServers": { "adx": { "command": "uv", "args": [ "--directory", "<full path to adx-mcp-server directory>", "run", "src/adx_mcp_server/main.py" ], "env": { "ADX_CLUSTER_URL": "https://yourcluster.region.kusto.windows.net", "ADX_DATABASE": "your_database" } } } }

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:

docker build -t adx-mcp-server .

Running with Docker

You can run the server using Docker in several ways:

Using docker run directly:

docker run -it --rm \ -e ADX_CLUSTER_URL=https://yourcluster.region.kusto.windows.net \ -e ADX_DATABASE=your_database \ -e AZURE_TENANT_ID=your_tenant_id \ -e AZURE_CLIENT_ID=your_client_id \ adx-mcp-server

Using docker-compose:

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

docker-compose up

Running with Docker in Claude Desktop

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

{ "mcpServers": { "adx": { "command": "docker", "args": [ "run", "--rm", "-i", "-e", "ADX_CLUSTER_URL", "-e", "ADX_DATABASE", "-e", "AZURE_TENANT_ID", "-e", "AZURE_CLIENT_ID", "-e", "ADX_TOKEN_FILE_PATH", "adx-mcp-server" ], "env": { "ADX_CLUSTER_URL": "https://yourcluster.region.kusto.windows.net", "ADX_DATABASE": "your_database", "AZURE_TENANT_ID": "your_tenant_id", "AZURE_CLIENT_ID": "your_client_id", "ADX_TOKEN_FILE_PATH": "/var/run/secrets/azure/tokens/azure-identity-token" } } } }

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 Docker with HTTP Transport

For HTTP mode deployment, you can use the following Docker configuration:

{ "mcpServers": { "adx": { "command": "docker", "args": [ "run", "--rm", "-i", "-p", "8080:8080", "-e", "ADX_CLUSTER_URL", "-e", "ADX_DATABASE", "-e", "ADX_MCP_SERVER_TRANSPORT", "-e", "ADX_MCP_BIND_HOST", "-e", "ADX_MCP_BIND_PORT", "adx-mcp-server" ], "env": { "ADX_CLUSTER_URL": "https://yourcluster.region.kusto.windows.net", "ADX_DATABASE": "your_database", "ADX_MCP_SERVER_TRANSPORT": "http", "ADX_MCP_BIND_HOST": "0.0.0.0", "ADX_MCP_BIND_PORT": "8080" } } } }

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:

curl -LsSf https://astral.sh/uv/install.sh | sh

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

uv venv source .venv/bin/activate # On Unix/macOS .venv\Scripts\activate # On Windows uv pip install -e .

Project Structure

The project has been organized with a src directory structure:

adx-mcp-server/ ├── src/ │ └── adx_mcp_server/ │ ├── __init__.py # Package initialization │ ├── server.py # MCP server implementation │ ├── main.py # Main application logic ├── Dockerfile # Docker configuration ├── docker-compose.yml # Docker Compose configuration ├── .dockerignore # Docker ignore file ├── pyproject.toml # Project configuration └── README.md # This file

Testing

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

Run the tests with pytest:

# Install development dependencies uv pip install -e ".[dev]" # Run the tests pytest # Run with coverage report pytest --cov=src --cov-report=term-missing

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.

Available Tools

Tool	Category	Description	Parameters
`execute_query`	Query	Execute a KQL query against Azure Data Explorer	`query` (string) - KQL query to execute
`list_tables`	Discovery	List all tables in the configured database	None
`get_table_schema`	Discovery	Get the schema for a specific table	`table_name` (string) - Name of the table
`sample_table_data`	Discovery	Get sample data from a table	`table_name` (string), `sample_size` (int, default: 10)
`get_table_details`	Discovery	Get table statistics and metadata	`table_name` (string) - Name of the table

Configuration

Required Environment Variables

Variable	Description	Example
`ADX_CLUSTER_URL`	Azure Data Explorer cluster URL	`https://yourcluster.region.kusto.windows.net`
`ADX_DATABASE`	Database name to connect to	`your_database`

Optional Environment Variables

Azure Workload Identity (for AKS)

Variable	Description	Default
`AZURE_TENANT_ID`	Azure AD tenant ID	-
`AZURE_CLIENT_ID`	Azure AD client/application ID	-
`ADX_TOKEN_FILE_PATH`	Path to workload identity token file	`/var/run/secrets/azure/tokens/azure-identity-token`

MCP Server Configuration

Variable	Description	Default
`ADX_MCP_SERVER_TRANSPORT`	Transport mode: `stdio` , `http` , or `sse`	`stdio`
`ADX_MCP_BIND_HOST`	Host to bind to (HTTP/SSE only)	`127.0.0.1`
`ADX_MCP_BIND_PORT`	Port to bind to (HTTP/SSE only)	`8080`

Logging

Variable

Description

Default

LOG_LEVEL

Logging level:

DEBUG

INFO

WARNING

ERROR