d365-dmf-mcp

MCP server that imports CSV files into Dynamics 365 F&O via Data Management (DMF). It runs locally and authenticates as the user signed in to the Azure CLI.

Setup on Windows

1. Install uv and the Azure CLI.

   winget install astral-sh.uv Microsoft.AzureCLI
   

2. Sign in with the account that has access to D365 (if there is no az session, the server falls back to an interactive browser login):

   az login --tenant <entra-tenant-id>
   

3. Register the server with Claude Code (runs the published package via uvx; see .mcp.json.example):

   claude mcp add d365-dmf `
     -e DMF_AZURE_TENANT_ID=<entra-tenant-id> `
     -e DMF_BASE_URL=https://<env>.sandbox.operations.eu.dynamics.com `
     -- uvx d365-dmf-mcp
   

   Other MCP clients: copy the block from .mcp.json.example into the client's MCP config. To run from a local checkout instead, use uvx --from C:\path\to\d365-dmf-mcp d365-dmf-mcp.

Tools

Only the tenant and environment URL are config. Everything else is passed per call.

• import_data(definition_group, company, files, format="CSV"): import one or more files into a data project and wait for the result. files is a list of {entity, file_path}; entity is the DMF entity name as shown in D365 (e.g. Customer groups) and the file (.csv or .xlsx) has the entity's field names (e.g. CUSTOMERGROUPID) in its first row. The server generates the package manifest, looks up each entity's target and the dependency order from D365, and creates the data project if it doesn't exist. format is free text (CSV, EXCEL, or any CSV/Excel-based D365 source format on the environment, e.g. CSV-Unicode).
• export_data(output_dir, definition_group, company): run an existing export data project and save its files.
• create_data_project(name, description=""): create an empty import data project (optional; import_data does this itself).
• list_data_projects(name_filter="", operation_type=""): browse existing data projects.
• list_project_entities(definition_group): the entities in a project, with format and execution order.
• search_entities(query, limit=50): search the DMF entity catalogue by name, target entity or module.
• get_entity_fields(entity): the column names (data file header), types, lengths and required flags for an entity.
• get_execution_status(execution_id): check the status of an execution, with errors if it failed.

Notes

• Composite and XML-based entities are not supported.
• Optional env vars: DMF_POLL_INTERVAL_SECONDS (default 5), DMF_POLL_TIMEOUT_SECONDS (default 300).