CategoryWeightCategory scoreContribution
Securityprompt, exec, net, exfil, eval
35%
35.0 pts
Supply chainhash, typosquat, maintainer, lockfile
20%
20.0 pts
Maintenancestaleness, pinning, CI
15%
15.0 pts
TransparencySKILL.md, perms, README
15%
15.0 pts
Communityinstalls, verify, response
15%
15.0 pts
Findings & checks · 0 flagged
Security
✓—All security checks passedNo findings in this category for the latest scan.pass
Supply chain
✓—All supply chain checks passedNo findings in this category for the latest scan.pass
Maintenance
✓—All maintenance checks passedNo findings in this category for the latest scan.pass
Transparency
✓—All transparency checks passedNo findings in this category for the latest scan.pass
Community
✓—All community checks passedNo findings in this category for the latest scan.pass
Every scanned point with the score it earned and what moved between them.
21b77fa
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Vault Retriever
Obsidian 知识库智能检索服务，为 AI 提供语义搜索和知识图谱分析能力。
特性
- 混合检索：BM25 关键词 + 向量语义 + RRF 融合 + PageRank 加权
- 轻量高效：mmap 索引加载，内存占用 ~300MB
- 后台索引：启动不阻塞，增量更新
- 零配置：开箱即用
安装
uv tool install vault-retriever --python 3.12工具列表
| 工具 | 说明 |
|---|---|
vault_search | 智能搜索笔记，融合关键词+语义+PageRank |
vault_read | 读取笔记完整内容 |
vault_list | 列出笔记，支持目录过滤和最近修改筛选 |
vault_links | 获取笔记的反向链接和出链关系 |
vault_tags | 获取标签统计或按标签查找笔记 |
vault_related | 查找语义相似的相关笔记 |
使用
Vault 路径配置
优先级：--vault 参数 > OBSIDIAN_VAULT_PATH 环境变量 > 当前目录
# 命令行参数
vault-retriever --vault /path/to/vault
# 环境变量
export OBSIDIAN_VAULT_PATH=/path/to/vault
vault-retrieverClaude Code 配置
命令行添加：
claude mcp add vault-retriever \
-e OBSIDIAN_VAULT_PATH=/path/to/vault \
-- vault-retriever项目 `.mcp.json`（放在 vault 目录下）：
{
"mcpServers": {
"vault-retriever": {
"type": "stdio",
"command": "vault-retriever",
"env": {
"OBSIDIAN_VAULT_PATH": "${PWD}"
}
}
}
}索引机制
- 启动时后台初始化（不阻塞主线程）
- BM25 索引使用 mmap 加载，内存高效
- 向量索引使用 LanceDB 持久化
- PageRank 图谱缓存到磁盘
- 每 10 分钟检查文件变动，增量更新
配置
在 vault 目录下创建 .obsidian/vault-retriever.json：
{
"embedding_model": "BAAI/bge-small-zh-v1.5",
"index_interval": 600
}embedding_model: 向量模型（默认 bge-small-zh-v1.5）index_interval: 索引更新间隔秒数（默认 600）
开发
git clone https://github.com/chyax98/vault-retriever.git
cd vault-retriever
uv sync
uv run vault-retriever --vault /path/to/vaultLicense
MIT