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Explorer/MCP/benzsevern/goldencheck
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GoldenCheck

benzsevern/goldencheck

Auto-discover validation rules from data — scan, profile, health-score. No rules to write.

19 tools available
The Journeyman
A reasonable amount of history and nothing concerning in the scan.
Time indexed (5mo)
19toolsRemote/ HTTP5moindexed
100% uptime · 310ms avgChecked Aug 9, 2026
Quality Score
69/95
Deep
Risk Score
0/100
Clean
How is this calculated?
Quality Breakdown
Tenure13.6/20
142 days indexed
Capability18.6/25
Tools: 6.6/13 (19 tools)
Description: 5/5
Endpoint: 7/7
Adoption11.9/25
Use count: 11.9/20 (917 uses)
Multi-registry: 0/5 (1 registry)
Reliability25/25
Currently live: 10/10
Uptime history: 15/15 100% (33/33 checks)
Security scan: 0 pts in v1.0; ready to weight when coverage improves
Risk
0Clean
No signals detected.
The scanner shows
19 tools. Registry verified. Nothing caught our attention.
First indexed Mar 27, 2026
Server Profile
Tools catalogued
19
19 tools available. Full list below.
Hosting
Remote / HTTP
Runs on the internet. No access to your filesystem, SSH keys, or environment variables.
Registry presence
Verified
Listed on the Official MCP Registry under Linux Foundation governance.
Liveness
100%
Based on 48 checks. Average response: 310ms.
Publisher Verification
✓ Listed on the Official MCP Registry under Linux Foundation governance.
Endpoint
https://goldencheck--benzsevern.run.tools
Tools (19)
scan
Scan a data file (CSV, Parquet, Excel) for data quality issues. Returns findings with severity, confidence, affected rows, and sample values. No configuration needed — rules are discovered from the data.
validate
Validate a data file against pinned rules in goldencheck.yml. Returns validation findings (existence, required, unique, enum, range checks).
profile
Profile a data file and return column-level statistics: type, null%, unique%, min/max, top values, detected formats. Also returns a health score (A-F) based on finding severity.
health_score
Get the health score (A-F, 0-100) for a data file. Quick summary of overall data quality.
list_checks
List all available profiler checks and what they detect. No arguments needed.
get_column_detail
Get detailed profile and findings for a specific column.
Show all 19 tools ↓
list_domains
List all available domain packs (healthcare, finance, ecommerce, etc.). Domain packs provide specialized semantic type definitions for specific data domains.
get_domain_info
Get detailed info about a specific domain pack — lists all semantic types, their name hints, and suppression rules.
install_domain
Download a community domain pack from the goldencheck-types repository and save it for use in future scans.
analyze_data
Analyze a data file to detect its domain, profile columns, and recommend a scanning strategy. Returns domain detection, column count, row count, strategy decisions, and alternative approaches.
auto_configure
Scan a data file, triage findings by confidence, and generate goldencheck.yml content from the pinned findings. Optionally accepts constraints to filter or adjust the generated config.
explain_finding
Explain a single finding in natural language. Requires the finding as a JSON dict and the file_path to load a profile for context.
explain_column
Get a natural-language health narrative for a specific column. Scans the file, profiles the column, and explains all findings.
review_queue
List all pending review items for a given job. Returns items that need human decision (medium-confidence findings).
approve_reject
Approve (pin) or reject (dismiss) a review queue item. Decision must be 'pin' or 'dismiss'.
compare_domains
Scan a file with every available domain pack (plus base/no-domain) and compare health scores. Recommends the best-fitting domain.
suggest_fix
Preview fixes for a data file without applying them. Shows what would change (columns, fix types, rows affected, before/after samples).
pipeline_handoff
Generate a structured quality attestation JSON for a data file. Includes health score, findings summary, pinned rules, and attestation status (PASS, PASS_WITH_WARNINGS, REVIEW_REQUIRED, FAIL).
review_stats
Get review queue statistics for a job — counts of pending, pinned, and dismissed items.

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