Load Jitbit data to DuckDB

Jitbit Helpdesk is a ticketing system that provides a REST API for managing support tickets, users, and categories. Everything needed to build a working Jitbit → 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.

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Build your Jitbit 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 Jitbit 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 Jitbit 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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Jitbit API at a glance

These values come from the Jitbit API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Jitbit API?

The API supports both Basic authentication and Bearer token authentication. For Basic auth, pass the 'Authorization' header as 'Basic ' followed by the base64-encoded 'username:password' string. For token auth, pass the 'Authorization' header as 'Bearer '.

1. Get your credentials

To authenticate with the Jitbit Helpdesk REST API, you can use either Basic Authentication (username and password) or Token-based Authentication. For Token-based Authentication: 1. Log in to your Jitbit Helpdesk web interface. 2. Navigate to https://<your_helpdesk_domain>/User/Token (or click your avatar in the top right and select 'API Token' if available). 3. Copy the token value provided. If you prefer Basic Authentication, use your standard Jitbit username (for on-premise installations, include the domain, e.g., 'DOMAIN\Username') and password. Note that changing your password will invalidate existing API tokens.

2. Add them to .dlt/secrets.toml

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[sources.jitbit_source]
api_username = "your_username"
api_password = "your_password"
# or for token-based auth
user_token = "your_user_token"

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 Jitbit data can I load into DuckDB?

These are the Jitbit endpoints dlt can load into DuckDB:

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How do I load only new Jitbit records?

The Jitbit API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.

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{"name": "tickets", "endpoint": {
    "path": "Tickets",
    # Replace with a field that increases on every write.
    "incremental": {"cursor_path": "REPLACE_ME", "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 Jitbit pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading Tickets and Ticket from the Jitbit API into DuckDB:

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

@dlt.source
def jitbit_source(api_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://<your_helpdesk_domain>/api",
            "auth": {"type": "bearer", "token": api_token},
        },
        "resources": [
            {"name": "tickets", "endpoint": {"path": "Tickets"}},
            {"name": "users", "endpoint": {"path": "Users"}}
        ],
    }
    yield from rest_api_resources(config)


def load_jitbit_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="jitbit_pipeline",
        destination="duckdb",
        dataset_name="jitbit_data",
    )
    load_info = pipeline.run(jitbit_source())
    print(load_info)


if __name__ == "__main__":
    load_jitbit_to_duckdb()

Run it with python jitbit_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 Jitbit 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):

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import dlt

data = dlt.pipeline("jitbit_pipeline").dataset()
df = data.tickets.df()
print(df.head())

SQL:

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SELECT * FROM jitbit_data.tickets LIMIT 10;

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

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How do I deploy the Jitbit 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 Jitbit 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 Jitbit 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