Load Freshsales data to DuckDB

Freshsales is a CRM platform providing a REST API for managing contacts, sales accounts, deals, tasks, and other sales-related resources. Everything needed to build a working Freshsales → 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 Freshsales 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 Freshsales 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 Freshsales 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.

---

Freshsales API at a glance

These values come from the Freshsales API reference — the authoritative source if anything here looks out of date.

---

How do I authenticate with the Freshsales API?

The API uses token-based authentication. The API key must be provided in the 'Authorization' header in the exact format 'Token token=<your_api_key>'.

1. Get your credentials

1. Sign in to your Freshworks CRM account at your account domain (e.g., https://yourcompany.myfreshworks.com). 2. Click on your profile picture in the top right corner and select Profile Settings. 3. Navigate to the API Settings tab. 4. Locate the API key field and copy your unique API key to your clipboard.

2. Add them to .dlt/secrets.toml

Copy
[sources.freshsales_source]
api_key = "your_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 Freshsales data can I load into DuckDB?

These are the Freshsales endpoints dlt can load into DuckDB:

---

How do I load only new Freshsales records?

The Freshsales API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.

Copy
{"name": "contacts", "endpoint": {
    "path": "api/contacts",
    # Replace with a field that increases on every write.
    "incremental": {"cursor_path": "REPLACE_ME", "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 Freshsales pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading contacts and deals from the Freshsales API into DuckDB:

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

@dlt.source
def freshsales_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://<bundle-alias>.myfreshworks.com/crm/sales/api",
            "auth": {"type": "api_key", "api_key": api_key, "name": "Authorization", "location": "header"},
        },
        "resources": [
            {"name": "contacts", "endpoint": {"path": "api/contacts", "data_selector": "contacts"}},
            {"name": "deals", "endpoint": {"path": "api/deals", "data_selector": "deals"}}
        ],
    }
    yield from rest_api_resources(config)


def load_freshsales_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="freshsales_pipeline",
        destination="duckdb",
        dataset_name="freshsales_data",
    )
    load_info = pipeline.run(freshsales_source())
    print(load_info)


if __name__ == "__main__":
    load_freshsales_to_duckdb()

Run it with python freshsales_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 Freshsales 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("freshsales_pipeline").dataset()
df = data.contacts.df()
print(df.head())

SQL:

Copy
SELECT * FROM freshsales_data.contacts LIMIT 10;

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

---

How do I deploy the Freshsales 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 Freshsales 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 Freshsales 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