A [Model Context Protocol][mcp] (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. [mcp]: https://m
Add this skill
npx mdskills install pab1it0/adx-mcp-serverWell-documented ADX/Kusto MCP server with comprehensive query and discovery tools
A Model Context Protocol (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.
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.
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
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:
AZURE_TENANT_ID and AZURE_CLIENT_ID environment variables setADX_TOKEN_FILE_PATHIf these environment variables are not present, the server will automatically fall back to DefaultAzureCredential, which tries multiple authentication methods in sequence.
{
"mcpServers": {
"adx": {
"command": "uv",
"args": [
"--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 ENOENTin Claude Desktop, you may need to specify the full path touvor set the environment variableNO_UV=1in the configuration.
This project includes Docker support for easy deployment and isolation.
Build the Docker image using:
docker build -t adx-mcp-server .
You can run the server using Docker in several ways:
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
Create a .env file with your Azure Data Explorer credentials and then run:
docker-compose up
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.
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"
}
}
}
}
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.
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 .
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
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:
When adding new features, please also add corresponding tests.
| 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 |
| 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 |
| 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 |
| 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 |
| Variable | Description | Default |
|---|---|---|
LOG_LEVEL | Logging level: DEBUG, INFO, WARNING, ERROR | INFO |
MIT
Install via CLI
npx mdskills install pab1it0/adx-mcp-serverAzure Data Explorer MCP Server is a free, open-source AI agent skill. A [Model Context Protocol][mcp] (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. [mcp]: https://m
Install Azure Data Explorer MCP Server with a single command:
npx mdskills install pab1it0/adx-mcp-serverThis downloads the skill files into your project and your AI agent picks them up automatically.
Azure Data Explorer MCP Server works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Gemini Cli, Amp, Roo Code, Goose. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.