Load LibreNMS data to DuckDB
Build a LibreNMS to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the LibreNMS API base URL, auth, endpoints, and incremental loading.
LibreNMS is a network monitoring system that provides a RESTful API for programmatic access to monitoring data and management functions. Everything needed to build a working LibreNMS → 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 LibreNMS to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from LibreNMS 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 LibreNMS 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.
LibreNMS API at a glance
| Base URL | https://your-librenms-instance.com/api/v0 |
| Example endpoint | GET api/v0/devices |
| Records found at | devices |
| Authentication | all requests require an X-Auth-Token header — sent in the X-Auth-Token header |
| Pagination | Not paginated |
| API reference | https://docs.librenms.org/API/ |
These values come from the LibreNMS API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the LibreNMS API?
All API requests must include an 'X-Auth-Token' HTTP header containing the user's API token. Tokens are generated through the LibreNMS web interface at the /api-access/ path.
1. Get your credentials
To obtain an API token for LibreNMS, follow these steps: 1. Log in to your LibreNMS web interface. 2. Navigate to the '/api-access/' page (often accessible via the Global Settings or User menu). 3. Click the 'Create API access token' button. 4. Select the user account you want to associate the token with. 5. Enter an optional description to identify the token later. 6. Click 'Create API Token' to generate the key. The token is shown once; ensure you copy it securely as it will not be displayed again.
2. Add them to .dlt/secrets.toml
[sources.librenms_source] api_token = "REPLACE_ME"
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 LibreNMS data can I load into DuckDB?
These are the LibreNMS endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| devices | /api/v0/devices | GET | devices | List all devices |
| services | /api/v0/services | GET | services | Retrieve all services |
| ports | /api/v0/ports | GET | ports | Retrieve all ports |
| inventory | /api/v0/inventory/:hostname | GET | inventory | Retrieve device inventory |
| device_groups | /api/v0/device_groups | GET | device_groups | Retrieve device groups |
How do I load only new LibreNMS records?
The LibreNMS 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.
{"name": "devices", "endpoint": { "path": "api/v0/devices", # 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 LibreNMS pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading '/api/v0/devices' and '/api/v0/system' from the LibreNMS API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def librenms_source(api_token=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://your-librenms-instance.com/api/v0", "auth": {"type": "api_key", "api_key": api_token, "name": "X-Auth-Token", "location": "header"}, }, "resources": [ {"name": "devices", "endpoint": {"path": "api/v0/devices", "data_selector": "devices"}}, {"name": "services", "endpoint": {"path": "api/v0/services", "data_selector": "services"}} ], } yield from rest_api_resources(config) def load_librenms_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="librenms_pipeline", destination="duckdb", dataset_name="librenms_data", ) load_info = pipeline.run(librenms_source()) print(load_info) if __name__ == "__main__": load_librenms_to_duckdb()
Run it with python librenms_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 LibreNMS 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):
import dlt data = dlt.pipeline("librenms_pipeline").dataset() df = data.devices.df() print(df.head())
SQL:
SELECT * FROM librenms_data.devices LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the LibreNMS 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 LibreNMS loads into governed, documented models.
- Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.
What other destinations can I load LibreNMS data to?
dlt loads into any of these — only the destination argument changes:
| Destination | Example value |
|---|---|
| PostgreSQL | "postgres" |
| BigQuery | "bigquery" |
| Snowflake | "snowflake" |
| Redshift | "redshift" |
| Databricks | "databricks" |
| Filesystem (S3, GCS, Azure) | "filesystem" |
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.
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