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Load Moesif data to DuckDB

Build a Moesif to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Moesif API base URL, auth, endpoints, and incremental loading.

SourceMoesifMoesif API DocumentationDestinationDuckDBIn-process analytical database. The default local destination for dlt pipelines.

Moesif is an API analytics and monetization platform that provides APIs for data collection and account management. Everything needed to build a working Moesif → 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 Moesif to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

Prompt
Run uvx dlthub-init@latest to build a pipeline from Moesif 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 Moesif 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.


Moesif API at a glance

Base URLhttps://api.moesif.net (Collector API) or https://api.moesif.com (Management API)
Example endpointGET v1/users
AuthenticationRequests require either an X-Moesif-Application-Id header or a Bearer token in the Authorization header depending on the API endpoint — sent in the Authorization header, prefixed Bearer
PaginationCursor-based next cursor at hits.hits.sort. The search API uses request body fields rather than query parameters for pagination. 'size' controls the number of records returned, and 'search_after' is used to provide the cursor for subsequent pages, derived from the 'sort' field of the last item in the previous response.
API referencehttps://www.moesif.com/docs/api

These values come from the Moesif API reference — the authoritative source if anything here looks out of date.


How do I authenticate with the Moesif API?

Authentication for the Collector API is provided via the X-Moesif-Application-Id header. For the Management API, authentication is handled using a Bearer token in the Authorization header.

1. Get your credentials

To obtain Moesif API credentials, log in to the Moesif Dashboard and navigate to the API Keys page (typically found under the account settings/gear icon menu at the bottom left). From there, you can view your Collector Application ID (for API monitoring and ingestion) or generate a new Management API Key (for administrative tasks and data retrieval). When generating a Management API Key, you can select specific scopes and set an expiration time.

2. Add them to .dlt/secrets.toml

[sources.moesif_source] moesif_application_id = "your_collector_application_id_here" moesif_management_api_key = "your_management_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 Moesif data can I load into DuckDB?

These are the Moesif endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
apps/v1/appsGETList applications
workspaces/v1/workspacesGETList workspaces
users/v1/usersGETList users
companies/v1/companiesGETList companies
subscriptions/v1/subscriptionsGETList subscriptions

How do I load only new Moesif records?

The Moesif 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": "users", "endpoint": { "path": "v1/users", # 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 Moesif pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading apps and events from the Moesif API into DuckDB:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def moesif_source(application_id=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.moesif.net (Collector API) or https://api.moesif.com (Management API)", "auth": {"type": "bearer", "token": application_id}, }, "resources": [ {"name": "users", "endpoint": {"path": "v1/users"}}, {"name": "companies", "endpoint": {"path": "v1/companies"}} ], } yield from rest_api_resources(config) def load_moesif_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="moesif_pipeline", destination="duckdb", dataset_name="moesif_data", ) load_info = pipeline.run(moesif_source()) print(load_info) if __name__ == "__main__": load_moesif_to_duckdb()

Run it with python moesif_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 Moesif 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("moesif_pipeline").dataset() df = data.users.df() print(df.head())

SQL:

SELECT * FROM moesif_data.users LIMIT 10;

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


How do I deploy the Moesif 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 Moesif 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 Moesif data to?

dlt loads into any of these — only the destination argument changes:

DestinationExample 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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