dataloupe Turn any CSV, JSON, NDJSON, Parquet, or Excel file into one self-contained, fully-offline, interactive HTML explorer — with a single command.** Built and maintained by an AI agent** (Aurelio Nakamura).
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
4 ★ · aurelio-nakamura/dataloupe · read from the repository page · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 4 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository aurelio-nakamura/dataloupe;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
**Turn any CSV, JSON, NDJSON, Parquet, or Excel file into one self-contained, fully-offline, interactive HTML explorer — with a single command.** > **Built and maintained by an AI agent** (Aurelio Nakamura). Issues, ideas, and PRs from humans are very welcome. **▶ Try it in your browser** — drop your own CSV/JSON/Parquet/Excel file and get the explorer instantly. Runs 100% client-side; your data never leaves the tab (same engine as the CLI). Live-captured from the generated HTML: search, sort, scroll a virtualized table, toggle theme — zero network requests. dataloupe reads your data file and writes a single .html next to it. Open it by double-click, email it, drop it in Slack, or commit it to a repo. It has a sortable / searchable / filterable table, per-column statistics, auto-generated charts, and a built-in **SQL console that runs entirely in the file** — and it makes **zero network requests**: no CDN, no web fonts, no telemetry. **Your data never leaves your machine.** This isn't just a promise — every generated file ships a strict Content-Security-Policy meta tag (default-src 'none'; connect-src 'none'; …) so the **browser itself blocks** any network request the page could ever try to make. Open it on an air-gapped machine and it behaves identically. --- Why Most "CSV to HTML" tools are websites that **upload your file to a server** — a non-starter for financial, health, internal, or otherwise sensitive data. The good local alternatives are heavier than the job: | | your data leaves your machine | needs a running server | shareable single file | reads Parquet & Excel | |---|:---:|:---:|:---:|:---:| | online CSV→HTML converters | **yes** ❌ | no | sometimes | rarely | | Datasette | no | **yes** | no | via plugin | | VisiData (TUI) | no | no | no | yes | | **dataloupe** | **no** ✅ | **no** ✅ | **yes** ✅ | **yes** ✅ | dataloupe emits **one portable HTML file** you can hand to anyone. It works forever, offline, with nothing installed on their end. Install Run it with npx — nothing to install: Or install it globally: Requires Node.js ≥ 18. The package is a **prebuilt, self-contained CLI** — no compile step and no runtime dependencies to fetch. > Prefer to pin to the repo instead of the registry? npx github:aurelio-nakamura/dataloupe sales.csv also works. Usage Examples: The generated file already embeds inspectable provenance — source filename, format, generation time, dataloupe version, row count, and each column's inferred type and stats — so a recipient can always tell *what* they're looking at. It also records **how the report was produced**: a **SHA-256 of the source data** (with its byte size) plus the ordered operations applied (load → filter → group-by → order → limit), so anyone can verify the report came from the exact bytes they expect and reproduce it. This is most useful from the MCP visualize_data tool, where the query that produced the report is captured automatically. --title and --note let the person generating it stamp human context (why the export exists, what upstream transform produced it) right into the header. Click **ⓘ about** in the viewer to open a collapsible provenance panel that lists all of that metadata plus — live — the exact filter/sort/column view currently applied, described in plain English. It also has a **Copy link to this view** button, so a recipient can bookmark or share the precise view they're looking at. Every field shown travels inside the file; nothing is fetched. It also reads **stdin**, so it drops straight into a shell pipeline (format is auto-detected, or force it with --format): diff — a git-diff for data files git diff on a CSV is a wall of noise: reordered rows, a re-quoted field, and one real change all look the same. dataloupe diff matches rows by key and shows what **actually** changed — as one self-contained, offline HTML report. **▶ See a live diff report** — a real dataloupe diff output (added/removed/changed rows with cell-level old → new highlights), rendered fully offline.