Load IOTA data to DuckDB

IOTA Core REST API provides a standard interface for interacting with IOTA node software including querying node state and network information. Everything needed to build a working IOTA → 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 IOTA 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 IOTA 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 IOTA 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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IOTA API at a glance

These values come from the IOTA 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 IOTA API?

Authentication uses a JWT token passed in the Authorization header with the Bearer prefix, e.g., 'Authorization: Bearer '.

1. Get your credentials

To obtain credentials for services like the IOTA Gas Station, sign up for an account or request access from the service operator. Log in to the operator's dashboard, navigate to the API keys or tokens section, and generate a new Bearer token. Store this token securely, as it will be required for authorization in API requests. Note that standard IOTA Core REST node endpoints are generally public and often do not require authentication, whereas specific services like the Gas Station require explicit Bearer token authorization.

2. Add them to .dlt/secrets.toml

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[sources.iota_source]
token = "your_gas_station_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 IOTA data can I load into DuckDB?

These are the IOTA endpoints dlt can load into DuckDB:

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How do I load only new IOTA records?

IOTA exposes cursor on transactions, 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": "transactions", "endpoint": {
    "path": "transactions",
    "data_selector": "nodes",
    "incremental": {"cursor_path": "cursor", "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 IOTA pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /api/core/v2/info and /api/core/v2/blocks from the IOTA API into DuckDB:

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

@dlt.source
def iota_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "http://127.0.0.1:14265",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "transactions", "endpoint": {"path": "transactions", "data_selector": "nodes"}},
            {"name": "checkpoints", "endpoint": {"path": "checkpoints", "data_selector": "nodes"}}
        ],
    }
    yield from rest_api_resources(config)


def load_iota_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="iota_pipeline",
        destination="duckdb",
        dataset_name="iota_data",
    )
    load_info = pipeline.run(iota_source())
    print(load_info)


if __name__ == "__main__":
    load_iota_to_duckdb()

Run it with python iota_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 IOTA 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("iota_pipeline").dataset()
df = data.transactions.df()
print(df.head())

SQL:

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SELECT * FROM iota_data.transactions LIMIT 10;

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

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How do I deploy the IOTA 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 IOTA 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 IOTA 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