Load UiPath Orchestrator data to DuckDB

UiPath Orchestrator is an enterprise automation management platform providing REST APIs to interact with resources, processes, and assets across different deployment models. Everything needed to build a working UiPath Orchestrator → DuckDB 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.

---

Build your UiPath Orchestrator to DuckDB pipeline

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

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from UiPath Orchestrator to DuckDB and run it on dltHub

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 UiPath Orchestrator 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.

---

UiPath Orchestrator API at a glance

These values come from the UiPath Orchestrator API documentation. Check them against the vendor's current reference before relying on them in production.

---

How do I authenticate with the UiPath Orchestrator API?

UiPath Orchestrator uses a Bearer token for authentication, which must be provided in the Authorization header of HTTP requests in the format 'Authorization: Bearer {access_token}'. Access tokens are typically obtained through OAuth 2.0 or legacy ROPC endpoints.

1. Get your credentials

1. Log in to your Automation Cloud account (cloud.uipath.com). 2. Navigate to Admin > Tenants. 3. Locate your Orchestrator service and click the three vertical dots (or the API Access icon). 4. Select API Access to view your Client ID, User Key (Refresh Token), Account Logical Name, and Tenant Name. These values are required to generate a temporary Bearer access token by making a POST request to https://account.uipath.com/oauth/token with a JSON body containing grant_type: 'refresh_token', client_id: '{client_id}', and refresh_token: '{user_key}'.

2. Add them to .dlt/secrets.toml

Copy
[sources.uipath_orchestrator_source]
client_id = "your_client_id_here"
refresh_token = "your_user_key_here"
tenant_name = "your_tenant_name_here"

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.

---

What UiPath Orchestrator data can I load into DuckDB?

These are the UiPath Orchestrator endpoints dlt can load into DuckDB:

---

How do I load only new UiPath Orchestrator records?

UiPath Orchestrator exposes CreationTime on odata/Jobs, 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.

Copy
{"name": "jobs", "endpoint": {
    "path": "odata/Jobs",
    "data_selector": "value",
    "incremental": {"cursor_path": "CreationTime", "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.

---

What does the generated UiPath Orchestrator pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /odata/Jobs and /odata/QueueDefinitions from the UiPath Orchestrator API into DuckDB:

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

@dlt.source
def uipath_orchestrator_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://cloud.uipath.com/{organizationName}/{tenantName}/orchestrator_",
            "auth": {"type": "bearer", "token": access_token},
        },
        "resources": [
            {"name": "jobs", "endpoint": {"path": "odata/Jobs", "data_selector": "value"}},
            {"name": "queue_items", "endpoint": {"path": "odata/QueueItems", "data_selector": "value"}}
        ],
    }
    yield from rest_api_resources(config)


def load_uipath_orchestrator_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="uipath_orchestrator_pipeline",
        destination="duckdb",
        dataset_name="uipath_orchestrator_data",
    )
    load_info = pipeline.run(uipath_orchestrator_source())
    print(load_info)


if __name__ == "__main__":
    load_uipath_orchestrator_to_duckdb()

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

---

How do I query UiPath Orchestrator data in DuckDB?

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):

Copy
import dlt

data = dlt.pipeline("uipath_orchestrator_pipeline").dataset()
df = data.jobs.df()
print(df.head())

SQL:

Copy
SELECT * FROM uipath_orchestrator_data.jobs LIMIT 10;

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

---

How do I deploy the UiPath Orchestrator to DuckDB 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 UiPath Orchestrator loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

---

What other destinations can I load UiPath Orchestrator 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.

---

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