Dataloupe
OCI · GHCR.IO/AURELIO-NAKAMURA/DATALOUPE:0.15.0
Offline MCP server to explore CSV/JSON/Parquet/Excel: preview, query, diff, render interactive HTML
Available components
Last scanned (11 hours ago)
Scores higher than 77% of OCI servers
Category Data and Analytics
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security0
- No malware scan is available for this kind of package: the supply-chain vendors we use do not cover it. This is a permanent gap in our coverage, not a finding about the package.Unverified
- Known CVEs could not be checked: this artifact ships no SBOM or dependency manifest, so there is no dependency list to read.Unverified
- Install-script risk not yet assessed.Unverified
- Dependency health could not be checked: this artifact ships no SBOM or dependency manifest, so there is no dependency list to read.Unverified
Provenance & Transparency35
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- License check failed: no license is declared. See how to fix → Fail
- Actively maintained (last published 64 days ago).Pass
- Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability65
- AI-judged instruction clarity (good).Pass
- Context-footprint check failed: tool/resource definitions use about 877 tokens (~125/item across 7 items; 7 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
- No destabilizing schema changes in the last 30 days.Pass
Tool Coverage92
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 77% of tool parameters carry a description.Partial
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 7 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 7 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Unverified: 1 category
A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 1 Nov 26 0
- Stability: 0.97 → pass security
- 31 Oct 26 0
- Stability: pass → 0.97 functional
- 23 Oct 26 0
- Stability: 0.97 → pass security
- 22 Oct 26 0
- Stability: pass → 0.97 functional
- 16 Oct 26 0
- Stability: 0.97 → pass security
- 15 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 13 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.
- 12 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 80 to 87. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 26 at this one. The score rises as the window fills, whether or not the server changes.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 5 Nov 2026 · Analysed oci/ghcr.io/aurelio-nakamura/dataloupe:0.15.0
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | oci |
| Reason | No attestation published |
Background: How many MCP packages publish verified provenance →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
describe_data Describe a data file ~87
Return the schema, row/column counts, and per-column statistics (type, nulls, unique, min/max/mean/median, top values) for a local data file. Token-efficient; reads a sample for very large files.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | Max rows to sample when profiling (default: all/auto). |
| path | string | yes | Path to the data file. |
No output schema declared.
No examples provided.
diff_data Diff two data files ~123
Compare two local data files (a git-style diff for data). Reports added/removed/changed/unchanged row counts (matched by --key when given), and optionally writes a self-contained offline HTML diff report. Both files stay local.
| Name | Type | Req | Description |
|---|---|---|---|
| after | string | yes | Path to the NEW file. |
| before | string | yes | Path to the OLD file. |
| key | array | – | Column(s) that uniquely identify a row (enables cell-level changes). |
| out_path | string | – | If set, write an offline HTML diff report here and return its path. |
No output schema declared.
No examples provided.
list_data_files List local data files ~60
List tabular data files (CSV/TSV/JSON/NDJSON/Parquet/Excel) in a local directory, with sizes.
| Name | Type | Req | Description |
|---|---|---|---|
| dir | string | yes | Directory to scan. |
| recursive | boolean | – | Recurse into subdirectories. |
No output schema declared.
No examples provided.
preview_data Preview rows ~56
Return the first N rows of a local data file as a Markdown table.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | Rows to show (default 20). |
| offset | integer | – | – |
| path | string | yes | Path to the data file. |
No output schema declared.
No examples provided.
query_data Query a data file ~156
Run a read-only structured query over a local data file: filter (where), select columns, order_by, limit/offset, and group_by with aggregations (count/sum/avg/min/max). Returns a Markdown table. No SQL, no writes — the file is never modified.
| Name | Type | Req | Description |
|---|---|---|---|
| aggregate | array | – | Aggregations to compute per group (with group_by). |
| group_by | array | – | Group rows by these columns. |
| limit | integer | – | – |
| offset | integer | – | – |
| order_by | object | – | – |
| path | string | yes | Path to the data file. |
| select | array | – | Columns to keep in the output. |
| where | array | – | Row filters (ANDed together). |
No output schema declared.
No examples provided.
sql_query Query a data file with SQL ~181
Run a read-only SQL SELECT over a local data file and get a Markdown table back. Supports: SELECT * | <cols> | aggregates COUNT/SUM/AVG/MIN/MAX, WHERE (=, !=, >, >=, <, <=, LIKE, IN) with AND, GROUP BY, ORDER BY [ASC|DESC], LIMIT, OFFSET. The table name in FROM is ignored (single-table). No writes, no arbitrary SQL execution — the query string is compiled to a safe read-only plan (no eval), and the file is never modified.
| Name | Type | Req | Description |
|---|---|---|---|
| path | string | yes | Path to the data file. |
| sql | string | yes | A single SELECT statement, e.g. `SELECT species, AVG(body_mass_g) AS avg_mass FROM t GROUP BY species ORDER BY avg_mass DESC LIMIT 5`. Column names must match the file's headers. |
No output schema declared.
No examples provided.
visualize_data Visualize as an offline interactive HTML explorer ~214
Turn a local data file (optionally after a query) into ONE self-contained, fully-offline, interactive HTML explorer file on disk (sortable/filterable table + column stats + charts). Returns the path. The user can open it in any browser; data never leaves the machine and the file has zero external requests. Use this to hand the user a shareable, explorable artifact instead of a plain text table.
| Name | Type | Req | Description |
|---|---|---|---|
| aggregate | array | – | Aggregations to compute per group (with group_by). |
| group_by | array | – | Group rows by these columns. |
| limit | integer | – | – |
| offset | integer | – | – |
| order_by | object | – | – |
| out_path | string | – | Where to write the .html (default: a temp file). |
| path | string | yes | Path to the data file. |
| select | array | – | Columns to keep in the output. |
| title | string | – | Title shown in the explorer. |
| where | array | – | Row filters (ANDed together). |
No output schema declared.
No examples provided.
How do I install the Dataloupe MCP server?
Dataloupe runs locally as a container image, launched with docker run --rm -i -e DATALOUPE_MCP_ROOT ghcr.io/aurelio-nakamura/dataloupe:0.15.0. Ready-made configuration for Claude, Cursor, VS Code, Codex and 3 more is on this page, copied from each client's own documentation.
oci · ghcr.io/aurelio-nakamura/dataloupe:0.15.0
claude mcp add aurelio-nakamura-dataloupe -- docker run --rm -i -e DATALOUPE_MCP_ROOT ghcr.io/aurelio-nakamura/dataloupe:0.15.0
This image reads DATALOUPE_MCP_ROOT. Set it in your client's env block for this server; docker run -e passes it through to the container.
What is the Dataloupe MCP server?
Dataloupe is an MCP server listed in the public MCP registry as io.github.aurelio-nakamura/dataloupe. Offline MCP server to explore CSV/JSON/Parquet/Excel: preview, query, diff, render interactive HTML. This page covers its container image (ghcr.io/aurelio-nakamura/dataloupe:0.15.0).
Is the Dataloupe MCP server safe to use?
Dataloupe scores 50 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Dataloupe MCP server expose?
Dataloupe exposes 7 tools: list_data_files, describe_data, preview_data, query_data, sql_query, and 2 more. Their descriptions and schemas cost roughly 877 tokens of context every time the server is loaded.
Is the Dataloupe MCP server still maintained?
Dataloupe is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.