Cinc Python API Docs | dltHub

CINC API is a REST API providing programmatic access to CINC CRM data including leads, agents, labels, notes, communications, webhooks and site configuration. The REST API base URL is https://public.cincapi.com/v2 and all requests require a Bearer access token (OAuth2).

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 pip install "dlt[workspace]" and start loading Cinc data in under 10 minutes.

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What data can I load from Cinc?

Here are some of the endpoints you can load from Cinc:

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How do I authenticate with the Cinc API?

CINC uses OAuth2 (authorization code grant) to obtain JWT-style access tokens. Include the token in requests using the Authorization header: Authorization: Bearer <access_token>.

1. Get your credentials

1. Register an integrator/app with CINC to obtain client_id and client_secret. 2) Direct users to the authorization endpoint: GET https://authv2.cincapi.com/integrator/authorize?client_id=...&response_type=code&redirect_uri=...&scope=api:read 3) After user consents, exchange the returned code for an access token by POSTing to https://authv2.cincapi.com/integrator/token with client_id, client_secret, grant_type=authorization_code, code and redirect_uri. 4) Save the access_token (and refresh_token) and use it in Authorization: Bearer <access_token>.

2. Add them to .dlt/secrets.toml

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[sources.cinc_source]
access_token = "your_oauth_access_token_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 venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

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dlt 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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dlt ai toolkit rest-api-pipeline install

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 Cinc 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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python cinc_pipeline.py

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

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Pipeline cinc_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset cinc_data
The duckdb destination used duckdb:/cinc.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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dlt pipeline cinc_pipeline 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 site_leads and site_agents from the Cinc 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 cinc_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://public.cincapi.com/v2",
            "auth": {
                "type": "bearer",
                "access_token": access_token,
            },
        },
        "resources": [
            {"name": "site_leads", "endpoint": {"path": "site/leads", "data_selector": "body"}},
            {"name": "site_agents", "endpoint": {"path": "site/agents", "data_selector": "body"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="cinc_pipeline",
        destination="duckdb",
        dataset_name="cinc_data",
    )
    load_info = pipeline.run(cinc_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("cinc_pipeline").dataset()
sessions_df = data.site_leads.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM cinc_data.site_leads LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("cinc_pipeline").dataset()
data.site_leads.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 Cinc 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

If the Authorization header is missing or the token expired, the API returns 401 Unauthorized. Ensure you exchange the authorization code for an access token and include: Authorization: Bearer <access_token>. Refresh tokens if expired via the integrator/token endpoint.

Rate limits

Responses include rate limit headers in the response header object: x-rate-limit-limit, x-rate-limit-remaining, x-rate-limit-reset. If you exceed limits, the API will return 429 Too Many Requests; back off and retry after x-rate-limit-reset.

Pagination

Paginated responses include a paging field in the response body with offset, limit, next and count. Use offset/limit or the paging.next token to request subsequent pages; when paging.next is null there are no more pages.

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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dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime install

• 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