Load Quip data to DuckDB

Quip provides REST-based Automation and Admin APIs for managing Quip content and administrative tasks using OAuth 2 authentication. Everything needed to build a working Quip → 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 Quip 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 Quip 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 Quip 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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Quip API at a glance

These values come from the Quip API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Quip API?

The API uses OAuth 2 for authentication and requires an 'Authorization' header in the format 'Bearer {{token}}' for all endpoints except specific authentication endpoints. The token itself is an access token obtained via Quip's OAuth 2 flow.

1. Get your credentials

1. Log in to your Quip site as an administrator and navigate to the Admin Console. 2. In the Admin Console, create a new API key. 3. Copy the 'Client ID' and 'Client Secret' provided. 4. Use these credentials with your preferred tool (e.g., Postman) to exchange them for an OAuth2 access token via the Token Endpoint (https://platform.quip.com/1/oauth/access_token). For personal testing, you may alternatively generate a personal access token directly through the platform interface. Note that for Admin API access, your user account must be explicitly added to the 'Admin API Users' list under Site Settings.

2. Add them to .dlt/secrets.toml

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[sources.quip_source]
access_token = "your_access_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 Quip data can I load into DuckDB?

These are the Quip endpoints dlt can load into DuckDB:

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How do I load only new Quip records?

Quip exposes min_last_modified_timestamp on admin/threads/list, 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": "threads_list", "endpoint": {
    "path": "admin/threads/list",
    "data_selector": "thread_ids",
    "incremental": {"cursor_path": "min_last_modified_timestamp", "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 Quip pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading threads_get and threads_export_status from the Quip API into DuckDB:

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

@dlt.source
def quip_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://platform.quip.com/1",
            "auth": {"type": "bearer", "token": access_token},
        },
        "resources": [
            {"name": "threads_list", "endpoint": {"path": "admin/threads/list", "data_selector": "thread_ids"}},
            {"name": "threads_recent", "endpoint": {"path": "threads/recent", "data_selector": "threads"}}
        ],
    }
    yield from rest_api_resources(config)


def load_quip_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="quip_pipeline",
        destination="duckdb",
        dataset_name="quip_data",
    )
    load_info = pipeline.run(quip_source())
    print(load_info)


if __name__ == "__main__":
    load_quip_to_duckdb()

Run it with python quip_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 Quip 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("quip_pipeline").dataset()
df = data.threads_recent.df()
print(df.head())

SQL:

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SELECT * FROM quip_data.threads_recent LIMIT 10;

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

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How do I deploy the Quip 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 Quip 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 Quip 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