Load OpenPhone data to DuckDB
Build a OpenPhone to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the OpenPhone API base URL, auth, endpoints, and incremental loading.
OpenPhone is a business communication platform offering a REST API for managing phone numbers, contacts, and messaging capabilities. Everything needed to build a working OpenPhone → 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.
Build your OpenPhone to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from OpenPhone 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 OpenPhone 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.
OpenPhone API at a glance
| Base URL | https://api.openphone.com/v1 |
| Example endpoint | GET messages |
| Records found at | data |
| Authentication | all requests require an API key in the Authorization header — sent in the Authorization header |
| Pagination | Cursor-based next cursor at nextPageToken, page size via maxResults |
| Incremental field | pageToken |
| API reference | https://www.quo.com/docs/mdx/api-reference/authentication |
These values come from the OpenPhone API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the OpenPhone API?
Authentication is performed by including the API key in the 'Authorization' header of every request. The API key must be sent verbatim; it is not a Bearer token.
1. Get your credentials
To obtain API credentials for the Quo (formerly OpenPhone) REST API, follow these steps: 1. Ensure you have an active workspace account with Owner or Admin privileges. 2. Log in to your Quo workspace. 3. Navigate to the Workspace Settings and locate the 'API' tab. 4. Click 'Generate API key' and assign a descriptive label to your key (e.g., 'production-integration'). 5. Copy the generated API key immediately, as it will be used in the Authorization header of your API requests (note: do not use 'Bearer' prefix).
2. Add them to .dlt/secrets.toml
[sources.openphone_source] api_key = "your_actual_api_key_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.
What OpenPhone data can I load into DuckDB?
These are the OpenPhone endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| phone_numbers | phone-numbers | GET | data | List all phone numbers associated with the account. |
| messages | messages | GET | data | Retrieve sent and received messages. |
| contacts | contacts | GET | data | List contact entries. |
| calls | calls | GET | data | Retrieve call records. |
| conversations | conversations | GET | data | Retrieve message history and threads. |
How do I load only new OpenPhone records?
OpenPhone exposes pageToken on messages, 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.
{"name": "messages", "endpoint": { "path": "messages", "data_selector": "data", "incremental": {"cursor_path": "pageToken", "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.
What does the generated OpenPhone pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading contacts and messages from the OpenPhone API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def openphone_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.openphone.com/v1", "auth": {"type": "api_key", "api_key": api_key, "name": "Authorization", "location": "header"}, }, "resources": [ {"name": "messages", "endpoint": {"path": "messages", "data_selector": "data"}}, {"name": "contacts", "endpoint": {"path": "contacts", "data_selector": "data"}} ], } yield from rest_api_resources(config) def load_openphone_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="openphone_pipeline", destination="duckdb", dataset_name="openphone_data", ) load_info = pipeline.run(openphone_source()) print(load_info) if __name__ == "__main__": load_openphone_to_duckdb()
Run it with python openphone_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.
How do I query OpenPhone 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):
import dlt data = dlt.pipeline("openphone_pipeline").dataset() df = data.messages.df() print(df.head())
SQL:
SELECT * FROM openphone_data.messages LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the OpenPhone 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 OpenPhone loads into governed, documented models.
- Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.
What other destinations can I load OpenPhone data to?
dlt loads into any of these — only the destination argument changes:
| Destination | Example value |
|---|---|
| PostgreSQL | "postgres" |
| BigQuery | "bigquery" |
| Snowflake | "snowflake" |
| Redshift | "redshift" |
| Databricks | "databricks" |
| Filesystem (S3, GCS, Azure) | "filesystem" |
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.
Next steps
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