Load 8x8 data to DuckDB

8x8 is a cloud communications provider offering various APIs for messaging, analytics, user management, and administration. Everything needed to build a working 8x8 → 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 8x8 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 8x8 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 8x8 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.

---

8x8 API at a glance

These values come from the 8x8 API reference — the authoritative source if anything here looks out of date.

---

How do I authenticate with the 8x8 API?

8x8 APIs primarily support either 'Authorization: Bearer {token}' or 'X-API-Key: {key}' headers depending on the specific API product. OAuth-based services require a preliminary POST request to obtain an access token.

1. Get your credentials

Log in to the 8x8 Admin Console. Navigate to the API Keys section (often located in the main application menu). Click on 'Create App', enter a unique name for the application, and select the specific API products you need access to. Save the configuration to generate your API Key and Secret. These credentials are used to obtain an access token via the 8x8 OAuth token endpoint.

2. Add them to .dlt/secrets.toml

Copy
[sources._8x8_source]
api_key = "your_8x8_app_key"
api_secret = "your_8x8_app_secret"

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 8x8 data can I load into DuckDB?

These are the 8x8 endpoints dlt can load into DuckDB:

---

How do I load only new 8x8 records?

8x8 exposes scrollId on users, 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.

Copy
{"name": "users", "endpoint": {
    "path": "users",
    "data_selector": "data",
    "incremental": {"cursor_path": "scrollId", "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 8x8 pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading https://api.8x8.com/admin-provisioning/users and https://api.8x8.com/oauth/v2/token from the 8x8 API into DuckDB:

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

@dlt.source
def _8x8_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.8x8.com (varies by product/service, e.g., /admin-provisioning)",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "users", "endpoint": {"path": "users", "data_selector": "data"}},
            {"name": "phone_numbers", "endpoint": {"path": "phone-numbers", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def load__8x8_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="_8x8_pipeline",
        destination="duckdb",
        dataset_name="_8x8_data",
    )
    load_info = pipeline.run(_8x8_source())
    print(load_info)


if __name__ == "__main__":
    load__8x8_to_duckdb()

Run it with python _8x8_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 8x8 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):

Copy
import dlt

data = dlt.pipeline("_8x8_pipeline").dataset()
df = data.users.df()
print(df.head())

SQL:

Copy
SELECT * FROM _8x8_data.users LIMIT 10;

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

---

How do I deploy the 8x8 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 8x8 loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

---

What other destinations can I load 8x8 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.

---

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