io.github.keshrath/agent-knowledge

MCPcommunity
v1.9.7io.github.keshrathUnknownUpdated 2mo agonpmGitHub

Cross-session memory for AI agents - knowledge graph, scoring, semantic search

Cross-session memory and recall for AI coding assistants -- works with Claude Code, Cursor, OpenCode, Cline, Continue.dev, and Aider out of the box. Git-synced knowledge base, hybrid semantic+TF-IDF search, auto-distillation with secrets scrubbing. Benchmark: R@5 = 97.2% (sparse) / 98.8% (hybrid) on and 86.0% (sparse) / 88.4% (hybrid) on the harder split — the public LongMemEval academic…

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2mo agoLast update
Package
Authorio.github.keshrath
LicenseUnknown
Version1.9.7
Sourcemcp-registry
npmagent-knowledge
GitHubkeshrath/agent-knowledge
Trust Status
A
95/100Trusted
✓Listed in Forge index+10/10
—Publisher identity verified+0/25
→ Publisher: run `forge publish` from the package repo to claim ownership
—Ed25519 publish signature+0/10
→ Included automatically when the publisher runs `forge publish`
—Domain verification+0/5
→ Publisher: host /.well-known/forge.json on the package homepage with { "publisher": "<github-login>" }
✓CVE scan · clean+30/30
✓Static analysis · clean+20/20
✓npm provenance (Sigstore)+5/5
Paste into Claude Code, Cursor, or any AI assistant to fix all gaps
StatusCommunity-indexed
PublisherUnverified
SignatureUnsigned
Domain—
Provenance✓ Sigstore-verified · f92dfae
Dependencies60 resolved · 1 with advisories
Tool surface6 tools · none privileged
Security scan✓ Cleanv1.9.7 · 20d ago
DEPws@8.20.0GHSA-58qx-3vcg-4xpx (transitive)
EvalsNone
IndexedJun 13, 2026

Verification confirms publisher identity (repo ownership), not code safety. The security scan covers known CVEs and suspicious install scripts — it cannot prove the absence of malicious code.

About

Cross-session memory and recall for AI coding assistants -- works with Claude Code, Cursor, OpenCode, Cline, Continue.dev, and Aider out of the box. Git-synced knowledge base, hybrid semantic+TF-IDF search, auto-distillation with secrets scrubbing. Benchmark: R@5 = 97.2% (sparse) / 98.8% (hybrid) on and 86.0% (sparse) / 88.4% (hybrid) on the harder split — the public LongMemEval academic benchmark (Wu et al. 2024, ICLR 2025), full 500 questions per split, no LLM, no API key, runs entirely…

Keywords
mcp