by sodam-ai · MCP Server · ★ 50
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AI에게 '정리해줘'라고 하면 흩어진 자료를 옵시디언(원본)에 노트로 정리하고, 관련 노트끼리 연결·분류·요약하고, 선택적으로 노션에 색인하는 Claude Code 플러그인 + 이식형 MCP 코어. 보관함 자동탐지·정리·자동 링크/MOC·자동 분류·요약(원자 노트)·검색(가짜 인용 방지)·볼트 건강검진(중복·깨진 링크·고아 탐지, 삭제 없는 안전 수정)·작업 로그. 사람 승인 게이트·원문 보존 알림·경로/프롬프트 인젝션 방어·무의존.
| Stars | 50 |
| Forks | 8 |
| Language | JavaScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 51.1212005998382/100 |
| Last Updated | 2026-09-11 |
| Created | 2026-06-07 |
| Platforms | claude-code, codex, gemini, mcp, node |
| Est. Tokens | ~13k |
These tools work well together with SoDam-WikiMate for enhanced workflows:
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Karpathy-style personal wiki for LLMs - markdown + frontmatter, no vector DB, no RAG. Built for Claude Code, w
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SoDam-WikiMate is AI에게 '정리해줘'라고 하면 흩어진 자료를 옵시디언(원본)에 노트로 정리하고, 관련 노트끼리 연결·분류·요약하고, 선택적으로 노션에 색인하는 Claude Code 플러그인 + 이식형 MCP 코어. 보관함 자동탐지·정리·자동 링크/MOC·자동 분류·요약(원자 노트)·검색(가짜 인용 방지)·볼트 건강검진(중복·깨진 링크·고아 탐지, 삭제 없는 안전 수정)·작. It is categorized as a MCP Server with 50 GitHub stars.
SoDam-WikiMate is primarily written in JavaScript. It covers topics such as ai-agent, claude-code, codex.
You can find installation instructions and usage details in the SoDam-WikiMate GitHub repository at github.com/sodam-ai/SoDam-WikiMate. The project has 50 stars and 8 forks, indicating an active community.
SoDam-WikiMate is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to SoDam-WikiMate on Agent Skills Hub include deterministic-agent-control-protocol, ChatCrystal, cognithor. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: