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Load World ID data to DuckDB

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

SourceWorld IDWorld ID API DocumentationDestinationDuckDBIn-process analytical database. The default local destination for dlt pipelines.

World ID is an identity service that provides REST API endpoints for verifying proof-of-humanity and managing application developer configurations. Everything needed to build a working World ID → 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 World ID 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 World ID 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 World ID 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.


World ID API at a glance

Base URLhttps://developer.world.org
Example endpointPOST api/v4/verify/{rp_id}
AuthenticationMost verification requests use path-based identification, while OIDC endpoints require Basic or Bearer authentication
PaginationNot paginated
API referencehttps://docs.world.org/world-id/reference/api-v4

These values come from the World ID API reference — the authoritative source if anything here looks out of date.


How do I authenticate with the World ID API?

Verification endpoints do not require authentication headers as they use path-based identifiers. For OIDC-related token and userinfo endpoints, authentication is handled via Basic Auth (using client_id:client_secret) or Bearer tokens respectively.

1. Get your credentials

To obtain API credentials for the World ID Developer Portal, follow these steps: 1. Navigate to the Developer Portal at https://developer.world.org. 2. Select your team. 3. Navigate to the API keys section in the dashboard. 4. Create or reset a team API key. 5. Copy the generated key immediately, as it is only displayed once. Team API keys for the developer portal start with the prefix api_.

2. Add them to .dlt/secrets.toml

[sources.world_id_source] world_developer_api_key = "api_your_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 World ID data can I load into DuckDB?

These are the World ID endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
developer_portal_verify/api/v4/verify/{rp_id}POSTVerifies World ID 4.0 and legacy 3.0 proofs
oidc_discovery/.well-known/openid-configurationGETOIDC discovery configuration
oidc_authorize/authorizeGETInitiates sign-in flow
oidc_token/tokenPOSTExchanges code for id_token
oidc_introspect/introspectPOSTIntrospects access token
oidc_userinfo/userinfoPOSTRetrieves user information

How do I load only new World ID records?

The World ID 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": "developer_portal_verify", "endpoint": { "path": "api/v4/verify/{rp_id}", # 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 World ID pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading verify and token from the World ID API into DuckDB:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def world_id_source(app_id=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://developer.world.org", "auth": {"type": "api_key", "api_key": app_id, "name": "token"}, }, "resources": [ {"name": "developer_portal_verify", "endpoint": {"path": "api/v4/verify/{rp_id}"}}, {"name": "oidc_token", "endpoint": {"path": "token"}} ], } yield from rest_api_resources(config) def load_world_id_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="world_id_pipeline", destination="duckdb", dataset_name="world_id_data", ) load_info = pipeline.run(world_id_source()) print(load_info) if __name__ == "__main__": load_world_id_to_duckdb()

Run it with python world_id_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 World ID 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("world_id_pipeline").dataset() df = data.developer_portal_verify.df() print(df.head())

SQL:

SELECT * FROM world_id_data.developer_portal_verify LIMIT 10;

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


How do I deploy the World ID 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 World ID 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 World ID 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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