1. Conduid
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  3. sovseal — Private AI Memory
MCP server · RAG

sovseal — Private AI Memory

Give Claude, Cursor, and every MCP client one shared memory that never leaves your machine. On-device vector search via LanceDB + Transformers.js (384-dim embeddings), AES-256-GCM client-side encryption, and write-behind ciphertext sync. ### What you can do 🧠 **Store memory** — embed and persist any context fact on-device. Automatic de-duplication, PII redaction, and write-behind encrypted sync. 🔍 **Recall memory** — semantic search over stored context. 10 ms warm recall, 0 RTT reads. Network is never on the read path. 📋 **Briefing context** — auto-summarized, reinforcement-aware briefing of procedural and semantic memories for bootstrapping new conversations. ### Tools - `store_memory` — embed content on-device (384-dim ONNX) → write local LanceDB → return. Ciphertext sync runs write-behind; nothing blocks. - `recall_memory` — embed query (LRU-cached) → vector search local LanceDB → top-K by L2 distance. 0 RTT. ### Resources - `sovseal://context/briefing` — summarized, reinfo

Unclaimed rag
34Low

Scored a month ago · breakdown

About sovseal — Private AI Memory

sovseal — Private AI Memory is an MCP server published by sovseal in the RAG category: give Claude, Cursor, and every MCP client one shared memory that never leaves your machine. On-device vector search via LanceDB + Transformers.js (384-dim embeddings), AES-256-GCM client-side encryption, and write-behind ciphertext sync. ### What you can do 🧠 **Store memory** — embed and persist any context fact on-device. Automatic de-duplication, PII redaction, and write-behind encrypted sync. 🔍 **Recall memory** — semantic search over stored context. 10 ms warm recall, 0 RTT reads. Network is never on the read path. 📋 **Briefing context** — auto-summarized, reinforcement-aware briefing of procedural and semantic memories for bootstrapping new conversations. ### Tools - `store_memory` — embed content on-device (384-dim ONNX) → write local LanceDB → return. Ciphertext sync runs write-behind; nothing blocks. - `recall_memory` — embed query (LRU-cached) → vector search local LanceDB → top-K by L2 distance. 0 RTT. ### Resources - `sovseal://context/briefing` — summarized, reinfo.

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Install

From source
git clone https://github.com/sovseal/mcp-server

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Questions

About sovseal — Private AI Memory

How do I install sovseal — Private AI Memory?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is sovseal — Private AI Memory safe to use with an AI agent?

Its trust score is 34 out of 100 (low). Conduid hasn't run static security checks on this repository yet, so review the source yourself before granting it credentials. It has no ConduID identity yet, so agent calls to it are not receipted.

Is sovseal — Private AI Memory still maintained?

Yes — the last commit was 2 months ago. The repository has 0 stars and 0 forks.