God's Eye View

Geospatial prototypes and data exploration

Use the globe to see whether several public sources answer a geographic question together before building a dedicated application. Inspect one known aircraft, one satellite and one event with source timestamps available. Missing coverage, delayed messages and a failed upstream request should be visible in your interpretation, even when the 3D scene remains visually convincing.

Public-data explainers and demonstrations

Build a camera tour that explains a route, an orbit, a weather pattern or infrastructure around a location. Keep observed data separate from simulated traffic and estimated camera geometry. For a published video, preserve provider credits and describe when the information was captured; a current-looking animation can contain older fallback data.

Agent-connected mapping experiments

The MCP setup guide connects a local running app to an agent client over STDIO. Browser-panel support depends on the client, and the panel build is a separate step. Test one location request, one entity query and a failed-provider case before incorporating the tools into an automated workflow.

Custom layers and geospatial services

The application construction API accepts explicit scene, controls, data and tool constructors. Forward search can use local coordinate parsing and bundled names before reaching configured geocoders. Integrators should own cancellation, cleanup, attribution and credential transport; the standalone app still allows only one instance per page.

Reproducible scene review

Record the checkout commit, enabled layers, optional keys, provider terms and capture time alongside a shared scene. URL state and a scene file reproduce the presentation more reliably than a verbal description, but changing live feeds can still produce a different result. Retain a static source-linked capture when exact historical evidence matters.

God's Eye View is a public-data visualization application for developers, geospatial enthusiasts and technical communicators. Its strength is bringing several independently sourced signals into one inspectable scene. It does not establish the completeness, accuracy or operational suitability of any individual feed, and the project should not be presented as a replacement for certified aviation, navigation or emergency systems.

Choose it when the task benefits from a navigable globe, source-level customization and a local agent interface. A conventional GIS workflow is a better fit for reproducible spatial analysis, coordinate-system management or a controlled geospatial data pipeline. For infrastructure metrics and SQL dashboards, Grafana and Apache Superset address different workloads.

The LICENSE file grants MIT terms for the source code, with separate terms for third-party datasets and models. GitHub currently labels the combined file NOASSERTION; that automated label does not erase the MIT text. Some bundled cable and event-imagery datasets are non-commercial, while OpenStreetMap-derived data has its own attribution and share-alike conditions. Review the particular assets you use rather than assuming one license covers the whole scene.

The software has no code purchase price. Local hardware, hosting and optional services can still cost money. Google Maps tiles, place search and voice providers can be metered; free provider plans have eligibility rules and quotas. The source and attribution ledger is the useful reference before enabling a feed or republishing its output.