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ktx-ai-data-agents-context

Skill Data & Analytics Solid

ktx is an executable context layer for data and analytics agents ๐Ÿ™ Allow Claude Code, Codex, and any AI agent to query data accurately through MCP with skills, memory and a semantic layer

835 starsApache-2.0 (commercial OK)FreeQuick setup

Reduces hallucination and query errors by providing AI agents a structured, executable context layer for database access. Enables accurate data retrieval at scale without manual prompt engineering or result validation overhead.

Data analytics teams and engineering leaders deploying AI agents that need reliable, governed access to production databases and data warehouses.

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https://github.com/Kaelio/ktx-ai-data-agents-context

By Kaelio

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
claude plugins install Kaelio/ktx-ai-data-agents-context

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

CostFree

Trust Signals Auto-scanned

Stars835Last updated2026-06-03LicenseApache-2.0 (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-06-03 · scanner v1

Community Pulse New

No community discussions found yet. This doesn't mean the tool isn't good โ€” it may be new or serve a niche use case.

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 835 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.

How to evaluate tools before deploying โ†’

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation

Ease of Use
4/5
Versatility
4/5
Reliability
3/5
Security
3/5
Overall score3.60 / 5.00 SolidEvaluatedJun 2026
Scored from trust signals (evidence-eval-v1): 835 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.

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