Load Connectwise-manage data to DuckDB

ConnectWise Manage REST API provides programmatic access to ConnectWise Manage data for integration purposes. Everything needed to build a working Connectwise-manage → 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 Connectwise-manage 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 Connectwise-manage 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 Connectwise-manage 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.

---

Connectwise-manage API at a glance

These values come from the Connectwise-manage API reference — the authoritative source if anything here looks out of date.

---

How do I authenticate with the Connectwise-manage API?

The API uses HTTP Basic authentication. The credentials must be a base64-encoded string of 'companyId+publicKey:privateKey'. This must be provided in the 'Authorization' header as 'Basic <base64_encoded_string>', and a 'clientId' header is also required.

1. Get your credentials

1. Log in to ConnectWise Manage as an administrator.
2. Navigate to System > Members.
3. Select the API Members tab.
4. Click the plus (+) icon to create a new API Member.
5. Fill in required fields (Member ID, Member Name, and choose a Role ID). For the Role ID, use 'Admin' for full access or a custom security role with restricted permissions.
6. Click Save to create the member.
7. With the new API member record open, click the API Keys tab.
8. Click the plus (+) icon to add a new API Key.
9. Enter a description for the key and click Save. 10. IMPORTANT: Copy and store the Public Key and Private Key immediately. The Private Key is only visible at this moment and cannot be retrieved once the screen is closed.

2. Add them to .dlt/secrets.toml

Copy
[sources.connectwise_manage_source]
company_id = "your_company_id"
public_key = "your_public_key"
private_key = "your_private_key"
base_url = "https://api-na.myconnectwise.net" # Adjust for your region/hosting (e.g., api-au.myconnectwise.net)

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 Connectwise-manage data can I load into DuckDB?

These are the Connectwise-manage endpoints dlt can load into DuckDB:

---

How do I load only new Connectwise-manage records?

Connectwise-manage exposes lastUpdated on company/companies, 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": "companies", "endpoint": {
    "path": "company/companies",
    "incremental": {"cursor_path": "lastUpdated", "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 Connectwise-manage pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading tickets and members from the Connectwise-manage API into DuckDB:

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

@dlt.source
def connectwise_manage_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://{your_connectwise_site}/v4_6_release/apis/3.0",
            "auth": {"type": "http_basic", "username": "REPLACE_ME", "password": api_key},
        },
        "resources": [
            {"name": "companies", "endpoint": {"path": "company/companies"}},
            {"name": "tickets", "endpoint": {"path": "service/tickets"}}
        ],
    }
    yield from rest_api_resources(config)


def load_connectwise_manage_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="connectwise_manage_pipeline",
        destination="duckdb",
        dataset_name="connectwise_manage_data",
    )
    load_info = pipeline.run(connectwise_manage_source())
    print(load_info)


if __name__ == "__main__":
    load_connectwise_manage_to_duckdb()

Run it with python connectwise_manage_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 Connectwise-manage 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("connectwise_manage_pipeline").dataset()
df = data.companies.df()
print(df.head())

SQL:

Copy
SELECT * FROM connectwise_manage_data.companies LIMIT 10;

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

---

How do I deploy the Connectwise-manage 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 Connectwise-manage 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 Connectwise-manage 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