Dynamics 365 Finance & Supply Chain Management Python API Docs | dltHub

Dynamics 365 Finance & Supply Chain Management provides a RESTful OData API to perform CRUD operations on data entities exposed within the application environment. The REST API base URL is https://[org].operations.dynamics.com/data and OAuth 2.0 authentication using Microsoft Entra ID with the client credentials grant flow is the standard method for service-to-service integration..

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv add "dlt[hub]" and start loading Dynamics 365 Finance & Supply Chain Management data in under 10 minutes.

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What data can I load from Dynamics 365 Finance & Supply Chain Management?

Here are some of the endpoints you can load from Dynamics 365 Finance & Supply Chain Management:

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How do I authenticate with the Dynamics 365 Finance & Supply Chain Management API?

Dynamics 365 Finance & SCM uses OAuth 2.0 with Microsoft Entra ID (Azure AD). Requests require an 'Authorization' header with the format 'Bearer {token}' obtained via the client credentials grant flow.

1. Get your credentials

To obtain credentials for the Dynamics 365 Finance & Supply Chain Management REST API, follow these steps: 1. Register an application in the Microsoft Entra ID (Azure AD) portal: Go to App registrations, click New registration, and note the Application (client) ID and Directory (tenant) ID. 2. Generate a client secret: In the App registration, navigate to Certificates & secrets, click New client secret, add a description/expiry, and copy the value immediately (it is only shown once). 3. Configure API permissions: In the app registration, go to API permissions, add the required Dynamics ERP permissions, and click Grant admin consent. 4. Register the app in your D365 environment: Log into your D365 instance, go to System administration > Setup > Microsoft Entra ID applications, click New, and add the Application (client) ID, a friendly Name, and the User ID (service account) you want the app to impersonate. Click Save to complete the configuration.

2. Add them to .dlt/secrets.toml

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[sources.dynamics_365_finance_supply_chain_management_source]
tenant_id = "your_tenant_id_here"
client_id = "your_client_id_here"
client_secret = "your_client_secret_here"
base_url = "https://your-instance.dynamics.com"
resource_url = "https://your-instance.dynamics.com"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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uv init
uv add "dlt[hub]"

1. Install the dlt AI harness:

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uv run dlthub ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

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uv run dlthub ai toolkit install rest-api-pipeline

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the Dynamics 365 Finance & Supply Chain Management API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

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uv run python dynamics_365_finance_supply_chain_management_pipeline.py

If everything is configured correctly, you'll see output like this:

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Pipeline dynamics_365_finance_supply_chain_management_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset dynamics_365_finance_supply_chain_management_data
The duckdb destination used duckdb:/dynamics_365_finance_supply_chain_management.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

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uv run dlthub show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

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Python pipeline example

This example loads /data and /api/services from the Dynamics 365 Finance & Supply Chain Management API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def dynamics_365_finance_supply_chain_management_source(client_credentials=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://[org].operations.dynamics.com/data",
            "auth": {"type": "bearer", "token": client_credentials},
        },
        "resources": [
            {"name": "data_entities", "endpoint": {"path": "data/{entity_name}", "data_selector": "value"}},
            {"name": "metadata", "endpoint": {"path": "data/$metadata", "data_selector": "value"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="dynamics_365_finance_supply_chain_management_pipeline",
        destination="duckdb",
        dataset_name="dynamics_365_finance_supply_chain_management_data",
    )
    load_info = pipeline.run(dynamics_365_finance_supply_chain_management_source())
    print(load_info)

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

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How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("dynamics_365_finance_supply_chain_management_pipeline").dataset()
sessions_df = data.data_entities.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM dynamics_365_finance_supply_chain_management_data.data_entities LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("dynamics_365_finance_supply_chain_management_pipeline").dataset()
data.data_entities.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

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What destinations can I load Dynamics 365 Finance & Supply Chain Management data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

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Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI harness:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-platform — Deploy, schedule, and monitor your pipeline in production.

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uv run dlthub ai toolkit install data-exploration
uv run dlthub ai toolkit install dlthub-platform

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack