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Load Karbon data to DuckDB

Build a Karbon to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Karbon API base URL, auth, endpoints, and incremental loading.

SourceKarbonKarbon API: Karbon Developer CenterDestinationDuckDBIn-process analytical database. The default local destination for dlt pipelines.

Karbon is a practice management platform that provides a REST API for managing work, contacts, and invoices. Everything needed to build a working Karbon → 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 Karbon to DuckDB pipeline

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

Prompt
Run uvx dlthub-init@latest to build a pipeline from Karbon 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 Karbon 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.


Karbon API at a glance

Base URLhttps://api.karbonhq.com/v3
Example endpointGET v3/Contacts
Records found atvalue
Authenticationall requests require Authorization Bearer token and AccessKey headers — sent in the Authorization header, prefixed Bearer
Also requiredAccessKey
PaginationCursor-based via @odata.nextLink (use the provided @odata.nextLink URL for the next request; no separate cursor parameter is sent), next cursor at @odata.nextLink, page size via $top (default 100, max 100). Karbon uses OData-style pagination. List endpoints include an @odata.nextLink URL when more results are available; you should follow that URL directly and not construct it manually (e.g., don’t manually increment $skip). You can also use $top (max 100) to control the number of items returned. $skip is used for offset-based paging but the recommended approach for the next page is to use @odata.nextLink.
Incremental fieldLastModifiedDateTime
API referencehttps://developers.karbonhq.com/guides/authentication/

These values come from the Karbon API reference — the authoritative source if anything here looks out of date.


How do I authenticate with the Karbon API?

Authentication requires two headers: 'Authorization' with a Bearer token and 'AccessKey' containing a JWT. Both credentials are obtained from the Karbon UI under Settings > Connected Apps > API Applications.

1. Get your credentials

  1. Log in to the Karbon application as an administrator. 2. Navigate to Settings, then select Connected Apps. 3. Select API Applications. 4. Choose your specific API Application or create a new one to generate credentials. 5. Copy the generated Authorization token (Bearer token) and the AccessKey.

2. Add them to .dlt/secrets.toml

[sources.karbon_source] token = "your_authorization_token_here" access_key = "your_access_key_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 Karbon data can I load into DuckDB?

These are the Karbon endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
invoicesv3/InvoicesGETvalueGets a list of Invoices
paymentsv3/PaymentsGETvalueGets a list of Payments
client_groupsv3/ClientGroupsGETvalueGets a list of Client Groups
contactsv3/ContactsGETvalueGets a list of Contacts
organizationsv3/OrganizationsGETvalueGets a list of Organizations

How do I load only new Karbon records?

Karbon exposes LastModifiedDateTime on v3/Contacts, 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.

{"name": "contacts", "endpoint": { "path": "v3/Contacts", "data_selector": "value", "incremental": {"cursor_path": "LastModifiedDateTime", "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 Karbon pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading v3/Users and v3/Contacts from the Karbon API into DuckDB:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def karbon_source(credentials=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.karbonhq.com/v3", "auth": {"type": "bearer", "token": credentials}, }, "resources": [ {"name": "contacts", "endpoint": {"path": "v3/Contacts", "data_selector": "value"}}, {"name": "invoices", "endpoint": {"path": "v3/Invoices", "data_selector": "value"}} ], } yield from rest_api_resources(config) def load_karbon_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="karbon_pipeline", destination="duckdb", dataset_name="karbon_data", ) load_info = pipeline.run(karbon_source()) print(load_info) if __name__ == "__main__": load_karbon_to_duckdb()

Run it with python karbon_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 Karbon 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):

import dlt data = dlt.pipeline("karbon_pipeline").dataset() df = data.contacts.df() print(df.head())

SQL:

SELECT * FROM karbon_data.contacts LIMIT 10;

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


How do I deploy the Karbon 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 Karbon 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 Karbon data to?

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

DestinationExample value
PostgreSQL"postgres"
BigQuery"bigquery"
Snowflake"snowflake"
Redshift"redshift"
Databricks"databricks"
Filesystem (S3, GCS, Azure)"filesystem"

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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