Kage vs Skill Seekers

Side-by-side comparison of two Model Context Protocol servers — install paths, tools, quality signals, and directory engagement so you can pick the right one for Claude, Cursor, and other MCP clients.

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K
Kage
kage-core
🧠 Knowledge & Memory
S
Skill Seekers
skill-seekers
🧠 Knowledge & Memory
SummaryVerified, git-native memory for coding agents. Memory is plain JSON packets committed in your repo, each checked against the code it cites — hallucinated citations rejected at write, stale or changed memory withheld at recall, plus diff-time stale-catch. Local-only (BM25 + vectors), no account, no API key. npx -y @kage-core/kage-graph-mcp installTransform 17 source types (docs, GitHub repos, PDFs, videos, Jupyter, Confluence, Notion, Slack/Discord) into AI-ready skills and RAG knowledge. 35 MCP tools for scraping, packaging, enhancing, and exporting to vector databases (Weaviate, Chroma, FAISS, Qdrant). Supports 16+ target platforms.
Quality signal24/100 (Emerging)33/100 (Emerging)
Install pathnpx · highnpx · low
Engagement 0 0 0 0 0 0 14,669
ToolsNot listed yetNot listed yet
Verified / officialNoNo
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