Load JSON Server data to DuckDB

JSON Server is a Node.js package that creates a full fake REST API from a JSON file, intended for prototyping and mocking backends for frontend development. Everything needed to build a working JSON Server → 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 JSON Server 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 JSON Server 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 JSON Server 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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JSON Server API at a glance

These values come from the JSON Server API documentation. Check them against the vendor's current reference before relying on them in production.

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How do I authenticate with the JSON Server API?

The core JSON Server does not provide native authentication. Authentication is typically added via the 'json-server-auth' middleware, which uses JWTs; the client must perform a POST request to a /login endpoint with email and password in the body to receive a token.

1. Get your credentials

Standard JSON Server instances do not provide a native dashboard or API key management system, as it is a development-only mock server. To secure your instance, you must manually implement authentication middleware (such as json-server-auth) in your project code to handle Authorization headers. If your specific environment requires a token, you must obtain it via the registration/login flow established in your custom middleware (e.g., POST requests to /login) and manually manage the credential in your dlt environment.

2. Add them to .dlt/secrets.toml

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[sources.json_server_source]
json_server_api_key = "your_bearer_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 JSON Server data can I load into DuckDB?

These are the JSON Server endpoints dlt can load into DuckDB:

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How do I load only new JSON Server records?

The JSON Server 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": "resources", "endpoint": {
    "path": "{resource}",
    # 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 JSON Server pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /users and /posts from the JSON Server API into DuckDB:

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

@dlt.source
def json_server_source(token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "http://localhost:3000",
            "auth": {"type": "bearer", "token": token},
        },
        "resources": [
            {"name": "resources", "endpoint": {"path": "{resource}", "data_selector": "data"}},
            {"name": "resource_item", "endpoint": {"path": "{resource}/{id}"}}
        ],
    }
    yield from rest_api_resources(config)


def load_json_server_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="json_server_pipeline",
        destination="duckdb",
        dataset_name="json_server_data",
    )
    load_info = pipeline.run(json_server_source())
    print(load_info)


if __name__ == "__main__":
    load_json_server_to_duckdb()

Run it with python json_server_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 JSON Server 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("json_server_pipeline").dataset()
df = data.resources.df()
print(df.head())

SQL:

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SELECT * FROM json_server_data.resources LIMIT 10;

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

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How do I deploy the JSON Server 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 JSON Server 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 JSON Server 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