- INVENTORY
- LOGIC
- MAP
- HUMAN
Short answer
How can I map my Azure Synapse dependencies using AI?
Your AI client pulls a full inventory of your datasets, linked services, and Spark notebooks. This gives you a clear view of how your data flows and where your logic lives.
The results.
Where your dependency data lands.
The AI organizes your workspace information into these specific views.
INVENTORY
Complete asset list
The AI gathers every dataset and linked service in your workspace. You get a clean list of what exists without manual clicking.
LOGIC
Notebook locations
The AI identifies all available Spark notebooks. This helps you see exactly where your transformation code is stored.
MAP
Dependency graph
By looking at linked services and datasets together, your AI builds a map of how your data moves through the pipeline.
HUMAN
Manual verification
The AI identifies the assets, but you decide which connections are broken or need updating. It flags the items, you make the calls.
The workflow
What your AI does when the connection is live.
The AI acts as a bridge between your workspace and your chat interface.
Scan datasets
The AI looks through your workspace to find every registered dataset.
list_datasetsCheck connections
It pulls a list of all linked services to see how your workspace talks to other storage or databases.
list_linked_servicesLocate notebooks
The AI finds all Spark notebooks to help you track your processing logic.
list_notebooksBuild the map
The AI correlates the datasets and services to explain your infrastructure layout.
list_datasetslist_linked_services
Try it
Copy these to start.
Use these prompts to begin your audit.
Starting points
These are basic requests. You can swap in specific workspace names or notebook titles to get more granular results.
Azure Synapse Analytics Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_MqO0WqrVDGRBLkpjn3kMhJJjBY9bjnhtsMU5bx9E/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Azure Synapse Analytics capabilities are ready to use.
{
"mcpServers": {
"azure-synapse-analytics-mcp": {
"url": "https://edge.vinkius.com/vk_preview_MqO0WqrVDGRBLkpjn3kMhJJjBY9bjnhtsMU5bx9E/mcp"
}
}
}List all the datasets in my Azure Synapse workspace.
Show me all the linked services currently configured.
Find all the Spark notebooks available in this workspace.
Map out the dependencies between my datasets and linked services.
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect Azure Synapse Analytics once, then ask.
Just link your account. Your credentials stay encrypted on our side, and you can immediately start asking questions about your data infrastructure.
Connect Azure Synapse Analytics to your AIFAQ
How this task behaves.
- 01
Can the AI delete my datasets?
No. This MCP only has read access to list your assets. It cannot delete, move, or modify anything in your workspace.
- 02
Can the AI run my Spark notebooks?
No. The AI can list the notebooks and their names, but it does not have the capability to execute the code inside them.
- 03
Does the AI see my actual data rows?
No. The AI only sees the metadata, such as dataset names and service configurations, not the raw data inside the files.
- 04
How does the AI know which notebooks exist?
It uses the list_notebooks tool to pull the names and locations of all notebooks in your workspace.
- 05
Can I use this to fix broken pipelines?
The AI can help you identify which linked services are present, but you must manually fix any connection issues in the Azure portal.
More questions about Azure Synapse Analytics? The Connector page answers them. See everything the Azure Synapse Analytics Connector can do
Connect Azure Synapse Analytics to Claude, Cursor, ChatGPT & more
