Load Ocean Protocol data to DuckDB

Ocean Protocol Provider is a REST API that handles data service provisioning, including encryption, decryption, and compute job management within the Ocean Protocol stack. Everything needed to build a working Ocean Protocol → 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 Ocean Protocol 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 Ocean Protocol 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 Ocean Protocol 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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Ocean Protocol API at a glance

These values come from the Ocean Protocol API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Ocean Protocol API?

The API supports an AuthToken mechanism where a JWT is passed in the 'AuthToken' request header. The token is obtained via the 'GET /api/services/createAuthToken' endpoint by signing a message containing the address and nonce.

1. Get your credentials

Ocean Protocol's Provider API does not use traditional static API keys for authentication. Instead, it utilizes signed authentication tokens to manage access securely. To obtain these credentials: 1) Generate a nonce for the current session. 2) Concatenate your Ethereum address and the nonce. 3) Sign this combined string using your Ethereum private key to generate a digital signature. 4) Send a GET request to the /api/services/createAuthToken endpoint with the address, nonce, expiration (future UTC timestamp), and the signature as query parameters. The response will return an AuthToken which you can then use in the request header (AuthToken: <your_token>) for subsequent API interactions.

2. Add them to .dlt/secrets.toml

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[sources.ocean_protocol_source]
auth_token = "REPLACE_ME"

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 Ocean Protocol data can I load into DuckDB?

These are the Ocean Protocol endpoints dlt can load into DuckDB:

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How do I load only new Ocean Protocol records?

The Ocean Protocol 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": "assets_query_post", "endpoint": {
    "path": "api/aquarius/assets/metadata/query",
    # 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 Ocean Protocol pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /api/services/createAuthToken and /api/services/deleteAuthToken from the Ocean Protocol API into DuckDB:

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

@dlt.source
def ocean_protocol_source(auth_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://v4.provider.oceanprotocol.com",
            "auth": {"type": "bearer", "token": auth_token},
        },
        "resources": [
            {"name": "assets_query_post", "endpoint": {"path": "api/aquarius/assets/metadata/query"}},
            {"name": "nonce", "endpoint": {"path": "api/services/nonce"}}
        ],
    }
    yield from rest_api_resources(config)


def load_ocean_protocol_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="ocean_protocol_pipeline",
        destination="duckdb",
        dataset_name="ocean_protocol_data",
    )
    load_info = pipeline.run(ocean_protocol_source())
    print(load_info)


if __name__ == "__main__":
    load_ocean_protocol_to_duckdb()

Run it with python ocean_protocol_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 Ocean Protocol 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("ocean_protocol_pipeline").dataset()
df = data.assets_query_post.df()
print(df.head())

SQL:

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SELECT * FROM ocean_protocol_data.assets_query_post LIMIT 10;

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

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How do I deploy the Ocean Protocol 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 Ocean Protocol 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 Ocean Protocol 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