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VecRecall 是一个进化版的 AI 长期记忆系统， v2.0 在纯向量检索之上，叠加 LLM 认知层（写入时自动抽取实体/关系/摘要/话题 + 语义去重）、时序知识图谱、遗忘曲线与主动蒸馏、多跳向量+图谱混合检索与静态加密，并把嵌入升级为「零依赖 subword 词法 + 多语言语义模型」双层。内置可复现评测集（21 组中英混合 query）中，召回率（R@5）达到 语义嵌入 100% / 零依赖词法 76.2%，为 AI Agent 提供更精准、更高效的上下文记忆支持。
vecRecall is an MCP server entry in ChatHome Skills, sourced from GitHub MCP Search and scored 51/100. VecRecall 是一个进化版的 AI 长期记忆系统， v2.0 在纯向量检索之上，叠加 LLM 认知层（写入时自动抽取实体/关系/摘要/话题 + 语义去重）、时序知识图谱、遗忘曲线与主动蒸馏、多跳向量+图谱混合检索与静态加密，并把嵌入升级为「零依赖 subword 词法 + 多语言语义模型」双层。内置可复现评测集（. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding vecRecall to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
git clone https://github.com/snowfoxHQ/vecRecall.gitReview the upstream source before running this command.
Scan coverage: Install metadata and repository README.
Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.
{
"fullName": "snowfoxHQ/vecRecall"
}VecRecall 是一个进化版的 AI 长期记忆系统， v2.0 在纯向量检索之上，叠加 LLM 认知层（写入时自动抽取实体/关系/摘要/话题 + 语义去重）、时序知识图谱、遗忘曲线与主动蒸馏、多跳向量+图谱混合检索与静态加密，并把嵌入升级为「零依赖 subword 词法 + 多语言语义模型」双层。内置可复现评测集（21 组中英混合 query）中，召回率（R@5）达到 语义嵌入 100% / 零依赖词法 76.2%，为 AI Agent 提供更精准、更高效的上下文记忆支持。