Dataset Explorer
PYPI · DATASET-EXPLORER-MCP
Local MCP analysis for CSV, TSV, Excel, JSON and Parquet: summaries, outliers and relationships.
Available components
Last scanned (11 hours ago)
Scores higher than 68% of PyPI 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 Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs setuptools.build_meta at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- 2 of 37 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency97
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to khanarmaghanrasheed-18/MCP-Dataset-Explorer). View diagnostics → Pass
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 26 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability33
- 0% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Fail
- AI-judged instruction clarity (fair).Partial
- Tool/resource definitions use about 323 tokens (~29/item across 11 items; 10 tools + 1 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
- Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
Tool Coverage71
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
- Structured output schemas are declared (80% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 10 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 11 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 +15
- Malware scan: unverified → pass ▲ security
- 31 Oct 26 −15
- Malware scan: pass → unverified ▼ security
- 29 Oct 26 +15
- Malware scan: unverified → pass ▲ security
- 26 Oct 26 −15
- Malware scan: pass → unverified ▼ security
- 25 Oct 26 +15
- Malware scan: unverified → pass ▲ security
- 23 Oct 26 −15
- Malware scan: pass → unverified ▼ security
- 17 Oct 26 +37
- Injection markers: unverified → pass ▲ security
- Malware scan: unverified → pass ▲ security
- First check of Judged manipulation: pass security
- Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window). security
- Tool coverage: unverified → 100 ▲ functional
- MCP protocol: unverified → pass ▲ functional
- Schema quality: unverified → 0 ▲ functional
- First check of Tool coverage: 0 functional
- First check of Schema quality: fail functional
- First check of Schema quality: fair functional
- First check of Tool coverage: 80 functional
- First check of Destructive annotations: pass functional
- First check of Schema quality: pass functional
- 16 Oct 26 −15
- Malware scan: pass → unverified ▼ security
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 pypi/dataset-explorer-mcp@0.2.2
Provenance Verified
A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.
| Result | Verified |
|---|---|
| Ecosystem | pypi |
| Reason | Verified |
| Discovered via | Registry attestation endpoint |
| Source repo | khanarmaghanrasheed-18/MCP-Dataset-Explorer |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/khanarmaghanrasheed-18/MCP-Dataset-Explorer/.github/workflows/release.yml@refs/heads/main |
| Rekor log index | 3165245576 |
| Predicate type | PyPI publish attestation https://docs.pypi.org/attestations/publish/v1 |
| Subject digest | sha256:8bca149ca586661a870f3f20dea7ee3604f12cd32bab00640a1daf6cb70ead4c |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | setuptools.build_meta |
Background: Why install scripts are a supply-chain risk →
Dependencies 37 packages
| Packages resolved | 37 |
|---|---|
| Stale | 2 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
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 →
analyze_missing_values ~25
Reports columns with missing values in the dataset.
| Name | Type | Req | Description |
|---|---|---|---|
| path | string | yes | – |
No output schema declared.
No examples provided.
analyze_target ~32
Gives a detailed summary of the target column.
| Name | Type | Req | Description |
|---|---|---|---|
| path | string | yes | – |
| target_name | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
dataset_shape ~26
Returns the number of rows and columns in a dataset.
| Name | Type | Req | Description |
|---|---|---|---|
| path | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
dataset_statistical_summary ~27
Returns the mean and median of every numerical feature.
| Name | Type | Req | Description |
|---|---|---|---|
| path | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
detect_outliers ~24
Detects Outliers in the dataset.
| Name | Type | Req | Description |
|---|---|---|---|
| path | string | yes | – |
No output schema declared.
No examples provided.
duplicate_finder ~23
Reports duplicate rows in the dataset.
| Name | Type | Req | Description |
|---|---|---|---|
| path | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
find_correlations ~35
Finds strongly correlated numerical feature pairs above a specified absolute threshold.
| Name | Type | Req | Description |
|---|---|---|---|
| path | string | yes | – |
| threshold | number | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
get_dataset_overview ~35
Returns dataset features, missing-value counts, categorical columns, numerical columns, and data types.
| Name | Type | Req | Description |
|---|---|---|---|
| path | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
inspect_Column ~35
Gives a detailed summary of a specific column/feature.
| Name | Type | Req | Description |
|---|---|---|---|
| col_name | string | yes | – |
| path | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
screen_target_relationships ~55
Screens numerical-numerical relationships with Pearson correlation and numerical-categorical relationships with correlation ratio eta squared. Screens categorical-categorical relationships with Cramer's V.
| Name | Type | Req | Description |
|---|---|---|---|
| path | string | yes | – |
| target | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
How do I install the Dataset Explorer MCP server?
Dataset Explorer runs locally as a PyPI package, launched with uvx dataset-explorer-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · dataset-explorer-mcp
claude mcp add khanarmaghanrasheed-18-dataset-explorer -- uvx dataset-explorer-mcp
What is the Dataset Explorer MCP server?
Dataset Explorer is an MCP server listed in the public MCP registry as io.github.khanarmaghanrasheed-18/dataset-explorer. Local MCP analysis for CSV, TSV, Excel, JSON and Parquet: summaries, outliers and relationships. This page covers its PyPI package (dataset-explorer-mcp).
Is the Dataset Explorer MCP server safe to use?
Dataset Explorer scores 71 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 5 November 2026. Its build provenance is signed and verified. 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 Dataset Explorer MCP server expose?
Dataset Explorer exposes 10 tools: get_dataset_overview, dataset_shape, dataset_statistical_summary, inspect_Column, analyze_target, and 5 more. Their descriptions and schemas cost roughly 317 tokens of context every time the server is loaded.
Is the Dataset Explorer MCP server still maintained?
Dataset Explorer 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.
What licence is the Dataset Explorer MCP server under?
Dataset Explorer declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.