Load Sage-accounting data to DuckDB

Sage Accounting is a cloud-based REST API for managing accounting entities like invoices, contacts, and bank transactions. Everything needed to build a working Sage-accounting → 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 Sage-accounting 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 Sage-accounting 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 Sage-accounting 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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Sage-accounting API at a glance

These values come from the Sage-accounting API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Sage-accounting API?

All API requests require an Authorization header with a Bearer token, a developer subscription key in the 'ocp-apim-subscription-key' header, and a 'Content-Type: application/json' header. Some operations may also require an 'X-Site' header to identify the resource owner (business).

1. Get your credentials

1. Navigate to the Sage Developer Portal at https://developer.sage.com/. 2. Sign up for a free developer account if you do not have one. 3. Log in to your developer dashboard. 4. Register a new application to obtain your 'Client ID' and 'Client Secret'. 5. During registration, define your 'Redirect URI' (the URL where Sage will send users after authorization). 6. Use these credentials to initiate the OAuth 2.0 authorization flow (direct users to the Sage authorization server to obtain an authorization code, then exchange it for an access token via a POST request to the token endpoint corresponding to the user's region).

2. Add them to .dlt/secrets.toml

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[sources.sage_accounting_source]
access_token = "your_access_token_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.

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What Sage-accounting data can I load into DuckDB?

These are the Sage-accounting endpoints dlt can load into DuckDB:

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How do I load only new Sage-accounting records?

Sage-accounting exposes updated_or_created_since on 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.

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{"name": "contacts", "endpoint": {
    "path": "contacts",
    "incremental": {"cursor_path": "updated_or_created_since", "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 Sage-accounting pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading api/v3/invoices and api/v3/contacts from the Sage-accounting API into DuckDB:

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

@dlt.source
def sage_accounting_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.accounting.sage.com/v3.1",
            "auth": {"type": "bearer", "token": access_token},
        },
        "resources": [
            {"name": "contacts", "endpoint": {"path": "contacts"}},
            {"name": "purchase_invoices", "endpoint": {"path": "purchase_invoices"}}
        ],
    }
    yield from rest_api_resources(config)


def load_sage_accounting_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="sage_accounting_pipeline",
        destination="duckdb",
        dataset_name="sage_accounting_data",
    )
    load_info = pipeline.run(sage_accounting_source())
    print(load_info)


if __name__ == "__main__":
    load_sage_accounting_to_duckdb()

Run it with python sage_accounting_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 Sage-accounting 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("sage_accounting_pipeline").dataset()
df = data.contacts.df()
print(df.head())

SQL:

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SELECT * FROM sage_accounting_data.contacts LIMIT 10;

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

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How do I deploy the Sage-accounting 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 Sage-accounting 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 Sage-accounting 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