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yantrikdb-server

Skill Data & Analytics Poor

Cognitive memory database for AI agents — consolidates duplicates, detects contradictions, fades stale memories via temporal decay. Rust, AGPL, ships as library / MCP server / HTTP cluster.

154 starsAGPL-3.0 (check with legal)FreeQuick setup
Below standard — Significant caveats apply. Not recommended without careful review of the security and evaluation sections.

Reduces hallucination and inconsistency in AI agent systems by maintaining coherent, deduplicated memory state with automatic stale-data purging—critical for production reliability in multi-turn workflows.

AI platform teams building stateful agents requiring consistent fact retrieval and contradiction detection across extended conversation histories.

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https://github.com/yantrikos/yantrikdb-server

By yantrikos

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 yantrikos/yantrikdb-server

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

CostFree

Trust Signals Auto-scanned

Stars154Last updated2026-05-31LicenseAGPL-3.0 (check with legal)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-06-05 · scanner v1

Community Pulse Growing

Discussed on Hacker News, Reddit

6 mentions across 2 sources

Reviewer notes

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

Scored from trust signals (evidence-eval-v1): 154 GitHub stars; contributors unknown; last commit 5d ago; license AGPL-3.0.

Things to check

  • License (AGPL-3.0) may restrict commercial use. Check with your legal team.

How to evaluate tools before deploying →

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
1/5
Versatility
3/5
Reliability
3/5
Security
3/5
Overall score2.30 / 5.00 PoorEvaluatedJun 2026
Scored from trust signals (evidence-eval-v1): 154 GitHub stars; contributors unknown; last commit 5d ago; license AGPL-3.0.

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