Azure Data Lake Storage MCP Server: Direct AI Access to Your Enterprise Data

Stop downloading files just to analyze them with Claude. This MCP server creates a direct bridge between your AI tools and Azure Data Lake Storage Gen2, giving you instant access to enterprise data without the download-upload dance.

Skip the File Shuffle

If you're working with data stored in ADLS2, you know the routine: download files locally, upload to Claude, analyze, repeat. It's tedious when you're dealing with large datasets or need to iterate quickly on analysis tasks.

This MCP server eliminates that friction entirely. Claude can directly read, write, and manipulate files in your ADLS2 storage account as if they were local files. Need to analyze a 50MB CSV sitting in your data lake? Claude accesses it directly. Want to save processed results back to a specific filesystem? Done in one step.

What You Get

Complete File System Operations: List filesystems, create directories, upload/download files, check existence, rename, move, and manage metadata - all through natural language commands to Claude.

Enterprise-Ready Authentication: Works with Azure CLI credentials for development or service principal authentication for production environments. Set it up once and forget about it.

Read-Only Safety Mode: Perfect for exploratory data analysis where you want to prevent accidental modifications to production data.

Seamless Claude Integration: Add one configuration block to Claude Desktop and you're accessing terabytes of enterprise data through conversational AI.

Real-World Usage Scenarios

Data Analysis Workflows: "Claude, analyze the sales data in /reports/2024/q1-sales.csv and create a summary report in /analysis/q1-summary.md" - Claude reads directly from ADLS2, processes the data, and saves results back.

Log File Investigation: Point Claude at your application logs stored in ADLS2. It can search, filter, and analyze log patterns without you having to download gigabytes of log files.

ETL Pipeline Monitoring: "Check if the latest data files exist in the /ingestion/ directory and validate their structure" - Claude can verify data pipeline outputs and flag issues.

Document Processing: Process Word docs, PDFs, or text files stored in your data lake. Claude reads them directly, extracts information, and can save processed results back to organized directory structures.

Quick Setup

Install with uv:

uv pip install adls2-mcp-server

Add to your Claude Desktop config:

{
    "mcpServers": {
        "adls2": {
            "command": "adls2-mcp-server",
            "env": {
                "AZURE_STORAGE_ACCOUNT_NAME": "your-storage-account",
                "READ_ONLY_MODE": "false"
            }
        }
    }
}

Authenticate with Azure CLI:

az login

That's it. Claude now has direct access to your ADLS2 storage.

Why This Matters

Enterprise data lives in cloud storage systems like ADLS2, but AI tools work best when they can access data directly. This server removes the artificial barrier between your AI assistant and your data infrastructure.

Instead of managing local copies, dealing with sync issues, or writing custom scripts to move data around, you get a standardized interface that just works. Your data stays where it belongs - in your enterprise storage - while your AI tools get the access they need to be genuinely useful.

The result? Faster iteration on data analysis, reduced manual file management, and AI that actually understands your enterprise data context.