Load Tenforce (Smart)List data to Microsoft Fabric

Tenforce is an EHSQ management software platform for manufacturing, utility, and government sectors that automates workflows and consolidates data across modules like audits, incidents, and document control. Everything needed to build a working Tenforce (Smart)List → Microsoft Fabric pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

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Build your Tenforce (Smart)List to Microsoft Fabric pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the Tenforce (Smart)List API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

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Tenforce (Smart)List API at a glance

These values come from the Tenforce (Smart)List API documentation. Check them against the vendor's current reference before relying on them in production.

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How do I authenticate with the Tenforce (Smart)List API?

Authentication is handled through identity providers such as Okta via protocols like OIDC or SAML, as the platform does not provide public REST API documentation for its primary EHSQ SaaS offering.

1. Get your credentials

TenForce integrates with enterprise identity providers such as Okta for Single Sign-On (SSO) and user provisioning. To obtain credentials for API access, you must contact your TenForce account administrator or the TenForce support team to request a service account or API-specific token. Navigate to your organization's user management or security settings dashboard in TenForce to manage authorized credentials, or request that they be generated via the administrative interface.

2. Add them to .dlt/secrets.toml

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[sources.tenforce_smart_list_source]
api_key = "your_api_key_here"
application_url = "https://your-instance.tenforce.com"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

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What Tenforce (Smart)List data can I load into Microsoft Fabric?

These are the Tenforce (Smart)List endpoints dlt can load into Microsoft Fabric:

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How do I load only new Tenforce (Smart)List records?

Tenforce (Smart)List exposes updated_at on api/smartlists, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "smart_lists", "endpoint": {
    "path": "api/smartlists",
    "data_selector": "items",
    "incremental": {"cursor_path": "updated_at", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

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What does the generated Tenforce (Smart)List pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading Tenforce.Contents and Lists (or specific list endpoints derived from the ListId parameter) from the Tenforce (Smart)List API into Microsoft Fabric:

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

@dlt.source
def tenforce_smart_list_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://www.tenforce.com",
            "auth": {"type": "api_key", "api_key": api_key, "name": "token", "location": "header"},
        },
        "resources": [
            {"name": "smart_lists", "endpoint": {"path": "api/smartlists", "data_selector": "items"}},
            {"name": "smart_list_details", "endpoint": {"path": "api/smartlists/{id}", "data_selector": "items"}}
        ],
    }
    yield from rest_api_resources(config)


def load_tenforce_smart_list_to_fabric() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="tenforce_smart_list_pipeline",
        destination="fabric",
        dataset_name="tenforce_smart_list_data",
    )
    load_info = pipeline.run(tenforce_smart_list_source())
    print(load_info)


if __name__ == "__main__":
    load_tenforce_smart_list_to_fabric()

Run it with python tenforce_smart_list_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query Tenforce (Smart)List data in Microsoft Fabric?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("tenforce_smart_list_pipeline").dataset()
df = data.smart_lists.df()
print(df.head())

SQL:

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SELECT * FROM tenforce_smart_list_data.smart_lists LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the Tenforce (Smart)List to Microsoft Fabric pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw Tenforce (Smart)List loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load Tenforce (Smart)List data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack