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Explorer/MCP/naver/datalab
REMOTE

Naver DataLab

naver/datalab

Korean search and shopping trend data from Naver DataLab. Pull relative search-volume curves for up to 5 keyword groups over a date range, or shopping-click trends by category, age, gender, and device.

6 tools available
The Journeyman
A reasonable amount of history and nothing concerning in the scan.
Time indexed (3mo)
6toolsRemote/ HTTP3moindexed
100% uptime · 347ms avgChecked Jun 30, 2026
Quality Score
45/95
Established
Risk Score
0/100
Clean
How is this calculated?
Quality Breakdown
Tenure12.3/20
90 days indexed
Capability16.3/25
Tools: 4.3/13 (6 tools)
Description: 5/5
Endpoint: 7/7
Adoption6/25
Use count: 6/20 (31 uses)
Multi-registry: 0/5 (1 registry)
Reliability10/25
Currently live: 10/10
Uptime history: 0/15 No checks yet
Security scan: 0 pts in v1.0; ready to weight when coverage improves
Risk
0Clean
No signals detected.
The scanner shows
6 tools. Nothing caught our attention.
First indexed May 18, 2026
Server Profile
Tools catalogued
6
6 tools available. Full list below.
Hosting
Remote / HTTP
Runs on the internet. No access to your filesystem, SSH keys, or environment variables.
Registry presence
Not verified
Not yet verified by the Official MCP Registry.
Liveness
100%
Based on 48 checks. Average response: 347ms.
Publisher Verification
Not yet verified by the Official MCP Registry.
Endpoint
https://datalab--naver.run.tools
Tools (6)
search_trends
Returns relative search volume over time for up to 5 keyword groups on Naver integrated search. Values are normalized so the largest bucket = 100.
shopping_category_trends
Returns relative shopping-click volume over time for up to 3 shopping-category groups.
shopping_keyword_trends
Returns relative click-volume trend for up to 5 keyword groups within a single shopping category.
shopping_age_breakdown
Returns shopping-click distribution by age bucket for one shopping category over time.
shopping_gender_breakdown
Returns shopping-click distribution by gender for one shopping category over time.
shopping_device_breakdown
Returns shopping-click distribution by device (pc vs mobile) for one shopping category over time.

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