GDAL + WhiteboxTools
Raster/vector conversion, hydrology, terrain, GeoPDF, NITF, COG authoring, tile generation and hundreds of Whitebox tools.
Extension seams, not core forks
Build at the right layer. Keep upgrades possible.
Extend the GeoLibre interface, call the platform API, add a compiled Go service or isolate specialist compute in a sidecar. Each seam has a different performance and lifecycle tradeoff.
Four extension layers
Match customization to its operational boundary.
The platform is deliberately not limited to one plugin language or one process model.
| Extension seam | Use it for | Contract | Tradeoff |
|---|---|---|---|
| GeoLibre frontend plugin | Panels, map tools, data-source browsers, renderers, workflows and client-side analysis | TypeScript/React components, plugin registration, shared map/project state and backend REST calls | Fastest UI iteration; browser security and memory constraints apply |
| Public API integration | Custom web apps, mobile clients, BI, automations and third-party systems | 600+ HTTP routes, OGC/Esri service surfaces, WebSockets and JSON/GeoJSON | Loose coupling; consumers must manage versioning, auth and network failure |
| Compiled Go service | High-throughput core capabilities, protocol handlers, persistent state and edge-resident processing | Backend package with explicit handlers and lifecycle registration | Highest performance and simplest deployment; changes ship with the server binary |
| Sidecar / worker service | Python ML, GDAL-heavy processing, proprietary SDKs, GPU jobs and organization-specific tools | HTTP/job contract, shared or object storage for artifacts, health and capability discovery | Independent dependencies and scaling; requires process supervision and observability |
GeoLibre plugin model
Extend the open frontend without replacing the platform.
GeoLibre uses MapLibre GL JS, deck.gl and an in-browser DuckDB path. More than 30 existing plugins demonstrate the intended integration pattern.
UI
Workflow panels and tools
Add navigation entries, panels, map interactions, editors, charts and specialized business workflows.
DATA
Source plugins
Connect catalogs such as NASA Earthdata, Microsoft Planetary Computer, USGS National Map, FEMA, Overture Maps and organization-specific APIs.
MAP
Layer and overlay adapters
Render raster, vector, MVT, PMTiles, COG, 3D Tiles, I3S, video and deck.gl analytical overlays through shared project state.
SQL
Browser analytical components
Use DuckDB-WASM and Pyodide workers for local processing while keeping large or privileged workloads on the backend.
SYNC
Web and desktop parity
The same frontend detects browser versus Wails desktop mode and calls the corresponding HTTP or native bridge path.
Sidecars as capability packs
Keep specialist runtimes optional and replaceable.
The Python server is a substantial capability pack, but the sidecar pattern is language-agnostic. A Rust, Java, .NET, GPU or proprietary-vendor service can follow the same boundary.
Scientific Python
rasterio, GeoPandas, scikit-learn, gstools, pykrige, OR-Tools, pvlib, xarray/virtualizarr and custom notebooks.
Model services
Object detection, wildlife/camera-trap analysis, acoustic classification, natural-language processing and local or OpenAI-compatible model routing.
Publication workers
Generate controlled DOCX, PDF and mapbook artifacts from approved mission baselines, with an HTML fallback when the sidecar is unavailable.
Organization-specific SDKs
Wrap systems that require their own runtime, license, GPU driver or update cadence instead of embedding them in the core process.
MCP-enabled capabilities
Register namespaced remote tools into the GeoAgent registry through MCP/JSON-RPC adapters while retaining tool identity and call boundaries.
Microservice boundary
Separate dependency risk without fragmenting the product.
The server remains the control plane for identity, catalog, data registration and client contracts. Sidecars perform bounded jobs and return portable artifacts or register a new service.
Core serviceAuth, TLS, rate limits, CORSCatalog and data connectionsOGC/Esri endpoint contractsJob request and health checks
→
Sidecar / workerVersioned request schemaProgress, cancellation and logsCPU/GPU/runtime isolationIdempotent artifact production
→
Registered outputGeoPackage / GeoParquetCOG / MBTiles / PMTiles3D Tiles / SLPKFeatureServer / MVT / STAC asset
Deployment profiles
One backend from central server to disconnected edge.
The headless server is a Wails-free Go build that boots the same application lifecycle as desktop and serves browser frontends plus APIs.
BIN
Native server binary
Run on bare Linux with a configured data directory, no GTK/WebKit GUI runtime and no mandatory Python process.
CTR
Docker container
Package the server and mount persistent data; place behind nginx or Traefik for routing and TLS termination.
LAN
On-premises service node
Share feature, tile, imagery, catalog and application services across a private network to desktop, browser and mobile clients.
EDGE
Disconnected deployment
Stage GeoPackage, MBTiles, PMTiles, COG, models and runtime assets so core mapping and analysis continue without cloud dependencies.
API
Baseline production controls
Bearer-token API auth, optional TLS with eager certificate validation, per-client token-bucket rate limiting, configurable CORS and /healthz readiness.
Enterprise hardening is deployment-specific.
For multi-tenant or regulated environments, add an external identity-aware proxy, SSO/OIDC, a secrets manager, centralized audit/log aggregation, backup/restore, vulnerability scanning, network policy and workload-specific high availability. These controls should be designed into the implementation plan rather than implied by a product logo.