Load Gmail Postmaster Tools API data to DuckDB

Gmail Postmaster Tools API provides programmatic access to email traffic metrics and domain verification status for email senders to Gmail users. Everything needed to build a working Gmail Postmaster Tools 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.

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Build your Gmail Postmaster Tools 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 Gmail Postmaster Tools 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 Gmail Postmaster Tools 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.

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Gmail Postmaster Tools API API at a glance

These values come from the Gmail Postmaster Tools API API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Gmail Postmaster Tools API API?

All requests must be authorized using OAuth 2.0 with a valid access token attached to the request, typically via an Authorization header with the Bearer scheme.

1. Get your credentials

1. Go to the Google Cloud Console (https://console.cloud.google.com/). 2. Create a new project or select an existing one. 3. Navigate to APIs & Services > Library and search for and enable the 'Postmaster Tools API'. 4. Go to APIs & Services > OAuth consent screen to configure your application's consent screen. 5. Navigate to APIs & Services > Credentials and click 'Create Credentials' > 'OAuth client ID'. 6. Select 'Desktop app' (or the appropriate type for your application) as the Application type. 7. Download the resulting JSON file containing your client ID and client secret, commonly saved as 'credentials.json'."},secrets_toml_example:{citations:,confidence:

2. Add them to .dlt/secrets.toml

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[sources.gmail_postmaster_tools_api_source]
client_id = "your_client_id_here"
client_secret = "your_client_secret_here"
token_path = "path/to/token.pickle"

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 Gmail Postmaster Tools API data can I load into DuckDB?

These are the Gmail Postmaster Tools API endpoints dlt can load into DuckDB:

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How do I load only new Gmail Postmaster Tools API records?

Gmail Postmaster Tools API exposes next_page_token on v2/domains, 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": "domains", "endpoint": {
    "path": "v2/domains",
    "data_selector": "domains",
    "incremental": {"cursor_path": "next_page_token", "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 Gmail Postmaster Tools API pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading domains and domainStats from the Gmail Postmaster Tools API API into DuckDB:

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

@dlt.source
def gmail_postmaster_tools_api_source(credentials=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://gmailpostmastertools.googleapis.com/",
            "auth": {"type": "bearer", "token": credentials},
        },
        "resources": [
            {"name": "domains", "endpoint": {"path": "v2/domains", "data_selector": "domains"}},
            {"name": "domain_users", "endpoint": {"path": "v2/{parent=domains/*}/users", "data_selector": "users"}}
        ],
    }
    yield from rest_api_resources(config)


def load_gmail_postmaster_tools_api_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="gmail_postmaster_tools_api_pipeline",
        destination="duckdb",
        dataset_name="gmail_postmaster_tools_api_data",
    )
    load_info = pipeline.run(gmail_postmaster_tools_api_source())
    print(load_info)


if __name__ == "__main__":
    load_gmail_postmaster_tools_api_to_duckdb()

Run it with python gmail_postmaster_tools_api_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 Gmail Postmaster Tools 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):

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import dlt

data = dlt.pipeline("gmail_postmaster_tools_api_pipeline").dataset()
df = data.domains.df()
print(df.head())

SQL:

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SELECT * FROM gmail_postmaster_tools_api_data.domains LIMIT 10;

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

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How do I deploy the Gmail Postmaster Tools 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 Gmail Postmaster Tools API 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 Gmail Postmaster Tools 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.

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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