Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Agent-native ecological data discovery, analysis, visualization, and provenance
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Die .mcpb-Datei des Entwicklers herunterladen
Der Link führt zur Datei des Entwicklers selbst; wir hosten sie nicht und verpacken sie nicht neu. Öffne die Datei, dann installiert Claude Desktop sie.
Führe das in deinem Terminal aus
Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto krnzt bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.1.0-alpha.1) kam vor 2 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du MCPB auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, AvaHR
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Read hiring data and create inactive assessment and questionnaire drafts for human review.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
WildDatum is a local-first ecological data workbench exposed as a standard Model Context Protocol server. It lets Codex, Claude, and other MCP agents discover, materialize, query, visualize, select, and cite scientific data without putting credentials, private paths, or millions of rows into model context.
NEON plus public ERDDAP services from EMSO ERIC, ICOS Carbon Portal, and Euro-Argo/Ifremer are built-in remote providers. Local tabular, raster, vector, point-cloud, image, hyperspectral, and N-dimensional array sources use the same provider-independent manifest, query, view, selection, and provenance model.
“Compare this NEON LiDAR tile with its hyperspectral cube. Show them together,
let me select an individual return or image pixel, then query the exact source
point or spectrum behind my selection.”
_A real WildDatum browser session using Rerun Web Viewer: a 6.6-million-point NEON LAS tile, a 500×500×107 reflectance cube, immutable provenance, and a verified selection mapped back to LAS source row 2,543,044._
scientific question
→ discover products, sites, and local assets → construct and approve a reproducible data plan → materialize immutable, checksum-verified sources → query and render a bounded multimodal Rerun view → human clicks, brushes, filters, or selects → WildDatum records that interaction as scientific state → agent queries the exact selected source data → export results, transformations, provenance, and citation
The visualization is not just a picture for the model to inspect. EcoViewSpec is authoritative view state and SemanticSelection is authoritative interaction state. A Rerun recording is a regenerable rendering artifact. For verified WildDatum point batches, an instance pick maps back to an exact LAS/LAZ source row; for a mapped cube, an image click maps back to the complete source spectrum. For linked trajectories and vertical profiles, a map or profile point maps back to the exact physical CSV/TSV, Parquet, or Arrow record, including provider-native QC values.
The main branch can now inspect the scientific structure of an existing local or materialized dataset without exposing its private path:
wilddatum inventory ds_...
wilddatum suggest-views ds_lidar... ds_cube... wilddatum create-suggested-view suggest_... ds_lidar... ds_cube... wilddatum resolve-selection-links sel_...
The equivalent registered MCP tools are inspect_scientific_inventory and suggest_views; create_view_from_suggestion accepts one of those opaque suggestion IDs, and resolve_selection_links evaluates applicable rules after a human selection. Inventories contain bounded fields, arrays, axes, units, CF/QC relationships, evidence, and unresolved decisions. Suggestions remain deterministic and side-effect free until accepted. On acceptance WildDatum recomputes the suggestion, rejects client-invented IDs, and persists an EcoViewSpec v2 with explicit scientific panels, encodings, and versioned link rules. Existing v1 views remain readable.
For the official NEON teaching pair, WildDatum reads the 107 measured wavelengths, selects bands nearest 650/550/450 nm, and ranks a 3D point-cloud + RGB + spectrum workspace first. Cube-pixel → spectrum is marked exact. WildDatum also extracts LAS WKT/GeoKey CRS metadata and the HDF5 EPSG, Map_Info, spatial extent, scale factor, and no-data value. The teaching cube's Map_Info origin disagrees with its declared reflectance extent by 500 m, and its footprint does not overlap the teaching LAS tile, so point → image pixel correctly remains unavailable for that pair instead of pretending that proximity is registration.
Accepted point-cloud + spectral-cube views render through the same pinned Rerun adapter and browser explorer as manually created views. The browser reports the view-spec version and panel/link counts. A cube-pixel pick automatically materializes its exact wavelength-aware spectrum as a durable result with the selection and link rule in its provenance. Unavailable link rules remain visible structured state and create no result rather than becoming guessed interactions. Link evaluation refuses stale selections after the view revision changes.
For datasets with the same authoritative CRS, an internally consistent north-up affine transform, and overlapping footprints, an exact point pick can now derive the source cube pixel and immediately chain into the complete wavelength-aware spectrum. The derived pixel, both link decisions, and the spectrum result remain inspectable through the normal MCP, CLI, and browser interfaces.
After resolution, the browser regenerates the authoritative view as a complete Rerun recording with a magenta source/derived pixel marker and the linked wavelength/value series inside its spectrum panel. The structured selection and result provenance still drive the overlay; the browser does not reconstruct it from canvas coordinates.
Linked trajectory/profile views now accept CSV, TSV, Parquet, GeoParquet, Arrow IPC, and Feather sources. One map can drive up to eight QC-aware value profiles. Inclusive depth/pressure/height ranges and deterministic per-profile point budgets reduce visual load while transparent source slots preserve exact Rerun-instance → physical-record identity for every displayed format.
Detailed support and caveats are in the format matrix. Design boundaries are documented in architecture and implementation decisions. Planned Research Infrastructure, visualization, and deployment work is tracked in the public roadmap.
The alpha ships self-contained macOS universal and Linux x86-64 packages. You do not need Rust, Node.js, CMake, or a separate Rerun installation:
curl -fsSL https://raw.githubusercontent.com/krnzt/wilddatum/v0.1.0-alpha.3/scripts/install.sh | sh
The installer verifies the release SHA-256, installs under ~/.local by default, and runs wilddatum setup. Set WILDDATUM_INSTALL_DIR to choose another prefix. If ~/.local/bin is not already on your PATH, add it before continuing.
Existing EcoScope alpha installations remain readable. WildDatum falls back to legacy ECOSCOPE_DATA_DIR, ECOSCOPE_CACHE_DIR, ECOSCOPE_WEB_DIST, default application-data directories, and NEON keychain entries when their WildDatum equivalents are absent. The installer also leaves an ecoscope command alias when it can do so without replacing a user-owned file.
Create a deterministic LiDAR + hyperspectral demonstration and open it in the bundled Rerun browser viewer:
wilddatum demo synthetic
The generated LAS and HDF5 files pass through the same import, manifest, cube mapping, Rerun recording, and selection-query paths as user data. No network or credentials are needed. An opt-in official NEON teaching-data demonstration is also available (roughly 224 MiB):
wilddatum demo neon --accept-download
WildDatum is published as io.github.krnzt/wilddatum in the official MCP Registry. It is also a normal local stdio server: Codex, Claude Code, and any compatible host launch the same wilddatum mcp process and discover its tools.
wilddatum register codex
wilddatum register claude
Both registration commands are safe to repeat and preserve an existing WildDatum entry. Platform-specific MCPB bundles are attached to every release for hosts and registries that install MCPB packages.
Equivalent host commands are:
codex mcp add wilddatum -- /absolute/path/to/wilddatum mcp
claude mcp add --scope user wilddatum -- /absolute/path/to/wilddatum mcp
Generic MCP configuration:
{
"mcpServers": { "wilddatum": { "command": "/home/you/.local/bin/wilddatum", "args": ["mcp"] } } }
After registration, the host launches WildDatum like any other local MCP server, negotiates the protocol, discovers its tools, and receives bounded structured results rather than bulk scientific files.
wilddatum import examples/observations.csv
wilddatum datasets wilddatum preview ds_... --limit 20 wilddatum create-view --name "Site comparison" ds_... wilddatum open view_...
Local paths are selected in the terminal, never passed as an MCP argument. The private SQLite registry retains the source path; agents receive an opaque ID, checksum, display name, scientific metadata, and provenance. The same path supports the raster, vector, point-cloud, image, and cube formats in the format matrix.
Profile/trajectory rendering is a validated recipe over ordinary CSV, TSV, Parquet, GeoParquet, Arrow IPC, or Feather data, not a provider-specific renderer. Start locally with the deterministic demo:
wilddatum demo profile-trajectory
The agent workflow is the same for a local import or materialized ERDDAP table:
user imports a compatible local table, or agent materializes a provider subset
→ create_view → configure_profile_trajectory_view → open_view → human selects a map or profile observation → inspect_view → query_selection → exact source record with native identifiers, values, units, and QC
The recipe explicitly names trajectory/profile identifiers, time, longitude, latitude, vertical coordinate and direction, one primary plus optional additional displayed values, units, fill values, and accepted native QC codes. It can also apply an inclusive source-coordinate vertical range and a per-profile display budget. WildDatum validates those fields against the source before authoring the exact-row mapping; the browser cannot declare a source index trusted, and sampling never changes the source instance slots.
_The shipped synthetic profile demo in Rerun Web Viewer. The sele
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