8x8 Python API Docs | dltHub

8x8 API is a platform that provides Communication Platform as a Service (CPaaS), Connect & Communication APIs, and Administration APIs for various communication and administrative functionalities. The REST API base URL is The 8x8 API uses multiple base URLs depending on the specific API and region, such as 'https://contacts.8x8.com/api/v1' for the Asia Contacts API and 'https://api.8x8.com/admin-provisioning' for the Site Management API. and All requests to the 8x8 Messaging API require an ApiKey Bearer Token for authentication..

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv add "dlt[hub]" and start loading 8x8 data in under 10 minutes.

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What data can I load from 8x8?

Here are some of the endpoints you can load from 8x8:

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How do I authenticate with the 8x8 API?

The 8x8 Messaging API uses an ApiKey Bearer Token authentication method, requiring the token to be sent in the Authorization header as 'Bearer <YOUR_API_KEY>'.

1. Get your credentials

To obtain API credentials, navigate to the 8x8 customer portal at https://connect.8x8.com/ and generate the necessary tokens.

2. Add them to .dlt/secrets.toml

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[sources._8x8_source]
token = "your_api_key_here"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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uv init
uv add "dlt[hub]"

1. Install the dlt AI Workbench:

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uv run dlthub ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

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uv run dlthub ai toolkit install rest-api-pipeline

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the 8x8 API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

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uv run python _8x8_pipeline.py

If everything is configured correctly, you'll see output like this:

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Pipeline _8x8_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset _8x8_data
The duckdb destination used duckdb:/_8x8.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

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uv run dlthub show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

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Python pipeline example

This example loads contacts and sites from the 8x8 API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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

@dlt.source
def _8x8_source(token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "The 8x8 API uses multiple base URLs depending on the specific API and region, such as 'https://contacts.8x8.com/api/v1' for the Asia Contacts API and 'https://api.8x8.com/admin-provisioning' for the Site Management API.",
            "auth": {
                "type": "bearer",
                "token": token,
            },
        },
        "resources": [
            {"name": "contacts", "endpoint": {"path": "contacts"}},
            {"name": "sites", "endpoint": {"path": "admin-provisioning/sites", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


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

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

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How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

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import dlt

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

SQL (DuckDB example):

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SELECT * FROM _8x8_data.contacts LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

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

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

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What destinations can I load 8x8 data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

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Troubleshooting

Authentication Failures

8x8 APIs, particularly the Messaging API, use an ApiKey Bearer Token authentication method. Ensure that your API key is correctly generated from the customer portal (https://connect.8x8.com/) and included in the Authorization header of your requests as 'Bearer <YOUR_API_KEY>'. Incorrect or expired tokens will result in authentication errors.

Pagination

For APIs like the Site Management API, endpoints such as /sites support pagination parameters like pageSize and pageNumber. When retrieving large datasets, ensure you are correctly implementing pagination to fetch all records. The response typically includes a pagination object with details like hasMore to indicate if further pages are available. Failure to handle pagination correctly may result in incomplete data retrieval.

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

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Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI Workbench:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-runtime — Deploy, schedule, and monitor your pipeline in production.

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uv run dlthub ai toolkit install data-exploration
uv run dlthub ai toolkit install dlthub-runtime

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack