mcp-adf — Azure Data Factory MCP server
One FastMCP server fronting one or more Azure Data Factory instances. Every tool takes a factory argument naming a target in connections.json; call list_factories first to see the configured targets.
Built on azure-mgmt-datafactory + azure-identity. Read tools work on any target; tools that create resources or trigger runs require the target to be flagged "writable": true.
Tools
Discovery / read (any target):
list_factories— configured targetsdiscover_factories— every ADF in a target's subscription (to fill in config)list_pipelines/get_pipelinelist_datasets/get_datasetlist_linked_services/get_linked_servicelist_triggers/get_trigger
Run monitoring / error analysis (any target):
list_pipeline_runs— run history over the last N days; filter by pipeline/statusget_pipeline_runlist_activity_runs— per-activity status / timing / error for a runanalyze_run_errors— run message + every failed activity's error code & message
Write (only against a "writable": true target):
create_or_update_linked_servicecreate_or_update_datasetcreate_or_update_pipelinerun_pipeline— trigger a run, returns the run_idcancel_pipeline_runstart_trigger/stop_trigger
Resource definitions are the JSON you see in ADF Studio's code view — pass either the full { "name": ..., "properties": {...} } object or just the inner properties object.
Configure
Copy connections.example.json to connections.json and fill in your targets:
{
"dev": {
"subscription_id": "00000000-0000-0000-0000-000000000000",
"resource_group": "rg-data-dev",
"factory_name": "adf-dev",
"auth": "azure-cli",
"writable": true
},
"prod": {
"subscription_id": "00000000-0000-0000-0000-000000000000",
"resource_group": "rg-data-prod",
"factory_name": "adf-prod",
"auth": "azure-cli",
"writable": false
}
}
connections.json and .env are gitignored — they never leave your machine.
Auth
Set "auth" per target:
| value | how it signs in | |-------|-----------------| | azure-cli (default) | reuses an az login token (requires Azure CLI) | | broker | Windows WAM broker popup (no CLI needed; great in tenants that block device-code flow) | | interactive | browser sign-in popup | | service-principal | app registration; secret read from client_secret_env (see .env.example) | | default | DefaultAzureCredential (env → cli → broker → …) |
The identity needs an ADF RBAC role on the factory — Data Factory Contributor for create/trigger, Reader for the read tools.
Setup
python -m venv .venv
.\.venv\Scripts\python.exe -m pip install -r requirements.txt
copy connections.example.json connections.json # then edit it
.\.venv\Scripts\python.exe server.py # smoke test (Ctrl+C to stop)
Finding your factories
discover.py signs in once and lists every subscription and the data factories in each, so you can fill in subscription_id / resource_group / factory_name:
.\.venv\Scripts\python.exe -m pip install azure-mgmt-subscription azure-mgmt-resource
.\.venv\Scripts\python.exe discover.py
Register with an MCP client
See examples/mcp.json:
{
"mcpServers": {
"adf": {
"command": "C:\\path\\to\\mcp-adf\\.venv\\Scripts\\python.exe",
"args": ["C:\\path\\to\\mcp-adf\\server.py"],
"env": {}
}
}
}
Use with Claude Desktop
Claude Desktop reads its MCP servers from claude_desktop_config.json. Open it from Settings → Developer → Edit Config (this creates the file if it doesn't exist), or edit it directly:
- Windows:
%APPDATA%\Claude\claude_desktop_config.json - macOS:
~/Library/Application Support/Claude/claude_desktop_config.json
Add this server under mcpServers, using absolute paths to the venv's Python and server.py:
{
"mcpServers": {
"adf": {
"command": "C:\\path\\to\\mcp-adf\\.venv\\Scripts\\python.exe",
"args": ["C:\\path\\to\\mcp-adf\\server.py"],
"env": {}
}
}
}
On macOS the paths are POSIX, e.g. "command": "/Users/you/mcp-adf/.venv/bin/python". Save the file and fully quit and reopen Claude Desktop (use Quit from the tray/menu-bar icon — closing the window isn't enough). The server's tools then appear in the tools (🔌) menu of a new chat.
License
MIT — see LICENSE.











