github verified Safe content atomic container

vecRecall

VecRecall 是一个改进版的 AI 长期记忆系统。它基于对原版 MemPalace 的深度分析重新构建,核心设计理念是将“信息检索”与“信息组织”彻底解耦。 通过纯向量检索路径和独立的 SQLite UI 层,VecRecall 在保持灵活组织的同时,将召回率(R@5)从原版的 84% 提升至 96.6%+,为 AI Agent 提供更精准、更高效的上下文记忆支持。

Cognium trust score
100%
Tier
Verified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.

Scan details: Circle-IR · 2026-09-19 · Appeal

View full trust & usage report →

Metadata

Version
1.0.0
Skill type
atomic
Execution layer
container
Category
database
Source
GitHub
Author type
human
Last scanned
2026-09-19
Updated
2026-09-21
View source Find related skills

Use via MCP

MCP

Resolve vecRecall from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
Swap --scope user for --scope project to commit it to .mcp.json.

Search SkillsRegistry