Load AG Grid data to DuckDB
Build a AG Grid to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the AG Grid API base URL, auth, endpoints, and incremental loading.
AG Grid is a client-side data grid library for JavaScript and frameworks that allows developers to implement custom server-side data fetching through their own backend APIs. Everything needed to build a working AG Grid → 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 AG Grid to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from AG Grid 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 AG Grid 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.
AG Grid API at a glance
| Base URL | N/A |
| Example endpoint | POST getRows |
| Records found at | rows |
| Authentication | no vendor authentication required; backend-specific authentication applies — sent in the request header |
| Pagination | Not paginated |
| Incremental field | startRow |
| API reference | https://dlthub.com/context/source/ag-grid |
These values come from the AG Grid API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the AG Grid API?
AG Grid is a client-side JavaScript library and does not have a vendor-provided REST API; authentication is entirely dependent on the backend implementation created by the user to serve data to the grid.
No credentials required. The AG Grid API is public, so there is nothing to obtain and nothing to add to .dlt/secrets.toml — the pipeline above runs as written.
What AG Grid data can I load into DuckDB?
These are the AG Grid endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| server_side_get_rows | getRows | POST | rows | Endpoint for Server-Side Row Model data requests. |
| infinite_scroll_get_rows | getRows | POST | rows | Endpoint for Infinite Scrolling Row Model data requests. |
| client_side_row_data | rows | GET | rows | Endpoint providing full dataset for Client-Side Row Model. |
| export_csv | export/csv | GET | Endpoint for triggering CSV export of grid data. | |
| export_excel | export/excel | GET | Endpoint for triggering Excel export of grid data. |
How do I load only new AG Grid records?
AG Grid exposes startRow on getRows, 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.
{"name": "server_side_get_rows", "endpoint": { "path": "getRows", "data_selector": "rows", "incremental": {"cursor_path": "startRow", "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 AG Grid pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading getRows and rows from the AG Grid API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def ag_grid_source(): config: RESTAPIConfig = { "client": { "base_url": "N/A", }, "resources": [ {"name": "server_side_get_rows", "endpoint": {"path": "getRows", "data_selector": "rows"}}, {"name": "client_side_row_data", "endpoint": {"path": "rows", "data_selector": "rows"}} ], } yield from rest_api_resources(config) def load_ag_grid_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="ag_grid_pipeline", destination="duckdb", dataset_name="ag_grid_data", ) load_info = pipeline.run(ag_grid_source()) print(load_info) if __name__ == "__main__": load_ag_grid_to_duckdb()
Run it with python ag_grid_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 AG Grid 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("ag_grid_pipeline").dataset() df = data.server_side_get_rows.df() print(df.head())
SQL:
SELECT * FROM ag_grid_data.server_side_get_rows LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the AG Grid 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 AG Grid 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 AG Grid 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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