Capsule-crm Python API Docs | dltHub

Capsule CRM is a CRM platform that provides a RESTful API to access and manage contacts, opportunities, projects, tasks, entries and related resources. The REST API base URL is https://api.capsulecrm.com/api/v2 and All requests require a Bearer token (OAuth2 or personal access token) in the Authorization header..

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 Capsule-crm data in under 10 minutes.

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What data can I load from Capsule-crm?

Here are some of the endpoints you can load from Capsule-crm:

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How do I authenticate with the Capsule-crm API?

API v2 uses OAuth2 bearer tokens; for quick/in‑house use you can generate a personal access token and include it as Authorization: Bearer {token} on every request.

1. Get your credentials

1. Sign in to your Capsule account. 2) For quick tokens: go to My Preferences → API Authentication Tokens → Generate new API token and copy the token. 3) For OAuth: register an application in developer/Apps to get client_id and client_secret, perform the OAuth2 authorization code flow at https://api.capsulecrm.com/oauth/authorise and exchange the code at https://api.capsulecrm.com/oauth/token.

2. Add them to .dlt/secrets.toml

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[sources.capsule_crm_source]
bearer_token = "your_personal_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 Capsule-crm 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 capsule_crm_pipeline.py

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

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Pipeline capsule_crm_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset capsule_crm_data
The duckdb destination used duckdb:/capsule_crm.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 capsule_crm_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 parties and opportunities from the Capsule-crm 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 capsule_crm_source(bearer_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.capsulecrm.com/api/v2",
            "auth": {
                "type": "bearer",
                "token": bearer_token,
            },
        },
        "resources": [
            {"name": "parties", "endpoint": {"path": "api/v2/parties", "data_selector": "parties"}},
            {"name": "opportunities", "endpoint": {"path": "api/v2/opportunities", "data_selector": "opportunities"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="capsule_crm_pipeline",
        destination="duckdb",
        dataset_name="capsule_crm_data",
    )
    load_info = pipeline.run(capsule_crm_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("capsule_crm_pipeline").dataset()
sessions_df = data.parties.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM capsule_crm_data.parties LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("capsule_crm_pipeline").dataset()
data.parties.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 Capsule-crm 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 bearer token is missing or invalid you will receive HTTP 401 Unauthorized. If the token lacks required scopes you will receive HTTP 403 Forbidden. Verify the Authorization: Bearer {token} header and ensure the token is active and scoped correctly.

Rate limits

Capsule enforces a per‑user limit of 4,000 requests per hour. Responses include X-RateLimit-Limit, X-RateLimit-Remaining and X-RateLimit-Reset headers. Exceeding the limit returns 429 Too Many Requests; pause requests until the reset time.

Pagination and incremental sync

List endpoints are paginated using page and pageSize (or next links). Use the since query parameter to fetch changes since a given timestamp and the dedicated "deleted" endpoints to reconcile removals.

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