Load Cambridge Dictionary data to DuckDB

The Cambridge Dictionary API provides programmatic access to dictionary content, search functionality, and thesaurus data for integration into external applications and websites. Everything needed to build a working Cambridge Dictionary → 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 Cambridge Dictionary 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 Cambridge Dictionary 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 Cambridge Dictionary 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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Cambridge Dictionary API at a glance

These values come from the Cambridge Dictionary API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Cambridge Dictionary API?

Authentication is handled by passing a custom 'accessKey' header with the API key in the request.

1. Get your credentials

To obtain credentials for the Cambridge Dictionary API, you must request access through their official portal. Visit the Cambridge Dictionaries Online API Developer Hub (https://dictionary-api.cambridge.org/) and navigate to the application form (https://dictionary-api.cambridge.org/apply). Complete the data licensing query form with details about your intended use case. Cambridge will review your request and, if approved, provide an API development key via email. Note that the API is a commercial service and is not available for free prototyping or general research; however, they may provide a 30-day evaluation key upon request for testing purposes.

2. Add them to .dlt/secrets.toml

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[sources.cambridge_dictionary_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.

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What Cambridge Dictionary data can I load into DuckDB?

These are the Cambridge Dictionary endpoints dlt can load into DuckDB:

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How do I load only new Cambridge Dictionary records?

The Cambridge Dictionary 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": "dictionaries", "endpoint": {
    "path": "dictionaries",
    # 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 Cambridge Dictionary pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading dictionaries and entries from the Cambridge Dictionary API into DuckDB:

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

@dlt.source
def cambridge_dictionary_source(accesskey=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://dictionary.cambridge.org/api/v1",
            "auth": {"type": "api_key", "api_key": accesskey, "name": "accessKey", "location": "header"},
        },
        "resources": [
            {"name": "dictionaries", "endpoint": {"path": "dictionaries"}},
            {"name": "entries", "endpoint": {"path": "dictionaries/{dictCode}/entries"}}
        ],
    }
    yield from rest_api_resources(config)


def load_cambridge_dictionary_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="cambridge_dictionary_pipeline",
        destination="duckdb",
        dataset_name="cambridge_dictionary_data",
    )
    load_info = pipeline.run(cambridge_dictionary_source())
    print(load_info)


if __name__ == "__main__":
    load_cambridge_dictionary_to_duckdb()

Run it with python cambridge_dictionary_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 Cambridge Dictionary 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("cambridge_dictionary_pipeline").dataset()
df = data.entries.df()
print(df.head())

SQL:

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SELECT * FROM cambridge_dictionary_data.entries LIMIT 10;

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

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How do I deploy the Cambridge Dictionary 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 Cambridge Dictionary 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 Cambridge Dictionary 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