Load CRS Credit API data to DuckDB

CRS Credit API is a credit data-as-a-service platform providing access to consumer and business credit reports across major bureaus through a single REST API. Everything needed to build a working CRS Credit API → 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 CRS Credit API 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 CRS Credit API 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 CRS Credit API 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.

---

CRS Credit API API at a glance

These values come from the CRS Credit API API reference — the authoritative source if anything here looks out of date.

---

How do I authenticate with the CRS Credit API API?

All requests require an API key provided in the Authorization header as a Bearer token (e.g., 'Authorization: Bearer <API_KEY>').

1. Get your credentials

1. Contact CRS sales or your account representative via the official website (https://crscreditapi.com/contact-us/) to discuss requirements and initiate the contract process. 2. Once the contract is executed and vetting/compliance is complete, you will be granted access to the CRS developer portal or account dashboard. 3. Log in to your account dashboard and navigate to the developer or API management section. 4. Generate or request your API credentials (API key). 5. Copy and store this key securely for use in your pipeline.

2. Add them to .dlt/secrets.toml

Copy
[sources.crs_credit_api_source]
api_key = "your_api_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 CRS Credit API data can I load into DuckDB?

These are the CRS Credit API endpoints dlt can load into DuckDB:

---

How do I load only new CRS Credit API records?

CRS Credit API exposes updated_at on v1/consumers, 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": "consumers", "endpoint": {
    "path": "v1/consumers",
    "data_selector": "consumers",
    "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.

---

What does the generated CRS Credit API pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /users/login and /v1/consumers from the CRS Credit API API into DuckDB:

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

@dlt.source
def crs_credit_api_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api-sandbox.stitchcredit.com",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "consumers", "endpoint": {"path": "v1/consumers", "data_selector": "consumers"}},
            {"name": "inquiries", "endpoint": {"path": "v1/inquiries", "data_selector": "inquiries"}}
        ],
    }
    yield from rest_api_resources(config)


def load_crs_credit_api_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="crs_credit_api_pipeline",
        destination="duckdb",
        dataset_name="crs_credit_api_data",
    )
    load_info = pipeline.run(crs_credit_api_source())
    print(load_info)


if __name__ == "__main__":
    load_crs_credit_api_to_duckdb()

Run it with python crs_credit_api_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 CRS Credit API 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("crs_credit_api_pipeline").dataset()
df = data.credit_reports.df()
print(df.head())

SQL:

Copy
SELECT * FROM crs_credit_api_data.credit_reports LIMIT 10;

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

---

How do I deploy the CRS Credit API 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 CRS Credit API 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 CRS Credit API 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