sovseal-memory MCP server
✓ VerifiedMenyediakan semantic memory berbasis local-first dan zero-knowledge untuk klien AI menggunakan on-device embeddings dan LanceDB.
Juga dikenal sebagai sovseal/core, core, @sovseal/mcp-server
- Stars
- 7
- Tools
- 2
- Unduhan, 30 hari
- —
- Versi terbaru
- 0.3.8
- Commit terakhir
- 5 Agu 2026
- Lisensi
- Apache-2.0
Apa itu sovseal-memory MCP?
sovseal-memory adalah MCP server. Menyediakan semantic memory berbasis local-first dan zero-knowledge untuk klien AI menggunakan on-device embeddings dan LanceDB. Server ini menyediakan 2 tool, seperti store_memory, recall_memory.
Ringkasan dibuat dari README proyek
Tentang sovseal-memory MCP server
sovseal-memory menyediakan solusi semantic memory berbasis local-first yang dirancang untuk pengguna yang menangani data sensitif seperti informasi hukum, kesehatan, atau fintech. Solusi ini memungkinkan klien AI untuk mempertahankan konteks yang persisten tanpa mengirimkan informasi plaintext ke cloud. Dengan menjalankan semua proses embedding dan recall pada hardware Anda sendiri, sistem ini memastikan data pribadi tidak pernah meninggalkan mesin Anda.
Server menggunakan LanceDB dan Transformers.js untuk melakukan on-device embeddings dengan model MiniLM 384-dimension. Setup ini memungkinkan latensi recall di bawah 25 ms karena pencarian semantik ditangani sebagai local vector queries, bukan melalui network calls. Sistem ini kompatibel dengan berbagai klien MCP termasuk Claude Desktop, Cursor, Windsurf, dan Zed, serta framework agent seperti ElizaOS dan CrewAI.
Pengguna dapat memilih antara mode local-only yang bekerja sepenuhnya secara offline atau tier sinkronisasi zero-knowledge opsional. Saat replikasi diaktifkan, sistem menggunakan enkripsi AES-256-GCM untuk memastikan hanya ciphertext yang dikirim ke server. Arsitektur ini memungkinkan adanya satu memori terpadu yang bekerja di berbagai platform melalui protokol MCP dan ekstensi browser pendamping.
Apa yang bisa Anda lakukan dengannya
- 1Menjaga privasi untuk industri sensitifDeveloper di bidang yang teregulasi dapat menggunakan memori AI tanpa melanggar NDA atau kebijakan residensi data.
- 2Menyatukan konteks di berbagai platform AIAnda dapat berbagi satu pool memori yang sama di antara berbagai antarmuka chat seperti ChatGPT dan Claude.
- 3Memungkinkan persistensi autonomous agentBangun framework agent yang mempertahankan state secara lokal tanpa harus menanggung biaya API per-call untuk embedding.
- 4Sinkronisasi memori antar perangkat secara amanReplikasi konteks AI Anda ke endpoint jarak jauh sambil memastikan server tidak dapat membaca data Anda.
Ditulis berdasarkan README proyek. Setiap use case diperiksa terhadap kutipan dari README tersebut.
Cara menginstal sovseal-memory MCP
Format diverifikasi 10 Nov 2026Instal sovseal-memory MCP di Claude Code
$ claude mcp add core -- npx -y @sovseal/mcp-serverInstal sovseal-memory MCP di Cursor
~/.cursor/mcp.json
{
"mcpServers": {
"core": {
"command": "npx",
"args": [
"-y",
"@sovseal/mcp-server"
]
}
}
}Instal sovseal-memory MCP di VS Code
.vscode/mcp.json
{
"servers": {
"core": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@sovseal/mcp-server"
]
}
}
}Instal sovseal-memory MCP di Claude Desktop
claude_desktop_config.json
{
"mcpServers": {
"core": {
"command": "npx",
"args": [
"-y",
"@sovseal/mcp-server"
]
}
}
}Instal sovseal-memory MCP di Codex
~/.codex/config.toml
[mcp_servers.core] command = "npx" args = ["-y", "@sovseal/mcp-server"]
Instal sovseal-memory MCP di Gemini CLI
~/.gemini/settings.json
{
"mcpServers": {
"core": {
"command": "npx",
"args": [
"-y",
"@sovseal/mcp-server"
]
}
}
}Tool sovseal-memory MCP 2
Terdeteksi dari READMEstore_memoryrecall_memory
| store_memory | — | |
| recall_memory | — |
Konfigurasi
SOVSEAL_ENDPOINTSOVSEAL_TRANSPORT
| Nama | Deskripsi | Tipe |
|---|---|---|
| SOVSEAL_ENDPOINT | — | |
| SOVSEAL_TRANSPORT | — |
Pengecekan otomatis
Berjalan 14 Nov 2026Laporan lengkap →Lolos checks otomatis kami. Ini bukan audit keamanan: baca kodenya dan berikan server akses paling terbatas yang dibutuhkannya. Cara kerja checks
- Source repository terhubung dan dapat dijangkausovseal/core is public and reachablegithub.com/sovseal/core ↗Lolos
- Paket menyebut repo ini sebagai sumbernya@sovseal/mcp-server names sovseal/core as sourcenpmjs.com/package/@sovseal/mcp-server ↗Lolos
- Provenance build (atestasi Sigstore)No build attestation published for this releaseTidak diperiksa
- Lisensi open source (OSI)Apache-2.0spdx.org/licenses/Apache-2.0.html ↗Lolos
- Ada commit atau release dalam satu tahun terakhirLast commit or release 2026-08-05github.com/sovseal/core ↗Lolos
- OpenSSF ScorecardTidak diperiksa
- Nama package tidak mirip dengan package populerNo popular package one edit away from @sovseal/mcp-serverLolos
- Tidak ada advisory kritis di paket maupun dependensinya235 resolved dependencies checked; no critical advisoryosv.dev ↗Lolos
- Tidak ada instruksi tersembunyi untuk model2 tool descriptions and the README read; no override phrases, credential paths or hidden charactersLolos
- Tools yang bersifat destruktif telah diberi labelNo tool named like delete, drop or execLolos
- Endpoint remote menjawab handshake MCPTidak diperiksa
README
Lihat di GitHubWhy this exists
If you work with code, clients, or data you're not allowed to upload — healthcare, legal, fintech, defense, or anything under an NDA — every AI memory option today asks you to break that rule. Platform memory keeps your context on their cloud, in their walled garden, one platform at a time. Cloud memory layers route your raw conversations through third-party servers and extraction APIs.
sovseal takes the other path: all capture, embedding, and recall run on your device. Plaintext never crosses the network. The optional sync tier ships only AES-256-GCM ciphertext — the server cannot read your memories even if it wanted to. And because it speaks MCP and rides a browser extension, it's one memory across every AI you use, not six silos.
Measured Performance & Benchmarks (May 2026)
Cloud-hosted memory layers force a tradeoff between latency, privacy, and cost. Every recall is a 200–800 ms round-trip to someone else's database. sovseal collapses the tradeoff. LanceDB and Transformers.js run inside your agent's process.
| Workload | Operation | p50 | p95 | p99 | Network |
|---|---|---|---|---|---|
| 10K records · 1K queries | recall_memory (warm) |
6.1 ms | 10.4 ms | 21.8 ms | 0 RTT |
| Cold start | recall_memory (first call) |
~1.2 s | — | — | 0 RTT |
| Single write | store_memory |
3.8 ms | 7.2 ms | 12.5 ms | 0 RTT (write-behind) |
All benchmarks reproduce with: pnpm --filter @sovseal/mcp-server run bench-v2 (10K pre-seeded memories, 1K sequential queries, CPU-bound ONNX embeddings on commodity hardware).
What makes it fast and private:
- Sub-25 ms p99 recall — semantic search is a local vector query, not an HTTP call.
- On-device embeddings — a pinned, hash-verified 384-dim MiniLM model (~22 MB quantized ONNX) runs locally. No embedding API, no per-call cost.
- Zero-knowledge sync — when replication is enabled, AES-256-GCM encryption happens before any byte leaves the device. The server stores ciphertext it cannot decrypt.
- Verified Semantic Recall (VSR) — every load re-derives
sha256(canonicalize(payload))and fails closed on mismatch. - Deterministic lineage — snapshot graph enables byte-equal state restoration.
Introduction
sovseal gives AI assistants and autonomous agents persistent, portable context that you actually own. It drops into any MCP-compatible client, captures from the major chat platforms via a browser extension, and keeps your plaintext where it belongs: on your hardware.
Key Features & Use Cases
Core Capabilities:
- Local-First Semantic Memory: On-device LanceDB + 384-dim Transformers.js embeddings for 0-RTT recall.
- Cross-Platform Capture: The browser extension captures and recalls across ChatGPT, Claude, Perplexity, Grok, Gemini, and DeepSeek — one memory, six platforms, ⌘/Ctrl+M anywhere.
- Zero-Knowledge Sync (optional): Replication ships only end-to-end AES-256-GCM ciphertext. Local-only mode works fully offline with no account.
- Write-Behind Replication: Tool calls return on local commit; ciphertext sync happens asynchronously.
- Developer-Friendly: Drop-in MCP server, Node SDK, and self-hosted edge endpoints.
Who it's for:
- Privacy-Constrained Teams: Healthcare, legal, fintech, and defense-adjacent teams whose policies require plaintext to stay on-device.
- AI Power Users: People working across Claude Desktop, Cursor, ChatGPT, and more who are tired of six AIs with six separate amnesias.
- Agent Frameworks: ElizaOS, Hermes, CrewAI, and LangGraph consume the MCP server natively — local memory with no per-call API bill.
⚖️ How sovseal compares
An honest map, because you'll ask anyway:
| Platform-native memory (ChatGPT / Claude) | Cloud memory layers (mem0, Zep, hosted MCP memories) | sovseal | |
|---|---|---|---|
| Where plaintext lives | Provider's cloud | Provider's cloud, or your servers (self-host = your ops) | Your device only |
| Extraction pipeline | Provider-internal | Typically an LLM API call on your raw text | On-device embeddings; no LLM in the loop |
| Works across platforms | No — each platform is a silo | Yes (via their cloud) | Yes — locally, via MCP + extension |
| Offline | No | No (cloud) / partial (self-host) | Yes |
| Sync model | Provider-controlled | Server reads your data | Server sees ciphertext only |
| Cost per recall | Subscription-gated | API/hosting cost | $0, local compute |
What you give up with sovseal, stated plainly: there's no cloud LLM doing clever extraction on your behalf (by design — that's the leak we exist to prevent), and you are responsible for your own key (see Threat Model). If neither of those matters to you and you live inside one platform, its native memory may be all you need. If they do matter, nothing else in this table does what the right-hand column does.
🚀 Quickstart Guide
Choose your path
sovseal exposes one protocol with three delivery shapes. Pick by where your code runs:
| MCP Server | Browser Extension | Node SDK / Self-Hosted | |
|---|---|---|---|
| Best for | Claude Desktop/Code, Cursor, Windsurf, Zed, agent frameworks | ChatGPT, Claude.ai, Perplexity, Grok, Gemini, DeepSeek in the browser | In-process use in a Node/TS service; full data residency |
| Install | npx -y @sovseal/mcp-server |
Chrome Web Store + local host installer | npm install @sovseal/sdk |
| Recall latency | 0 RTT (local LanceDB) | 0 RTT (Native Messaging to local engine) | 0 RTT (local LanceDB) |
| Cost | Free (Hobby) | Free (Hobby) | Paid (Starter or above for self-hosted sync) |
MCP Server
The default for AI coding assistants and any agent framework that speaks MCP. One server binary, one config snippet, every client.
Claude Desktop, Cursor, Windsurf, Zed — add to mcp.json or claude_desktop_config.json:
{
"mcpServers": {
"sovseal-memory": {
"command": "npx",
"args": ["-y", "@sovseal/mcp-server"]
}
}
}
One-line install for Claude Code:
claude mcp add sovseal -- npx -y @sovseal/mcp-server
System Prompt Snippet (Claude Desktop / Cursor Project Instructions): To ensure the AI natively uses the memory server, paste this into your custom instructions:
This session has persistent memory via sovseal. At conversation start, check the sovseal://context/recent resource. Whenever the user shares preferences, plans, or personal context, store it via store_memory.
For always-on autonomous agents, switch to HTTP/SSE transport so the sovseal process outlives a single tool invocation:
SOVSEAL_TRANSPORT=sse SOVSEAL_PORT=4040 npx -y @sovseal/mcp-server
Browser Extension
For the AI platforms that don't speak MCP. The extension bridges ChatGPT, Claude.ai, Perplexity, Grok, Gemini, and DeepSeek to the same on-device engine over Native Messaging — capture-on-send as you chat, ⌘/Ctrl+M to recall anywhere, with per-site toggles and one-click delete.
- Install from the Chrome Web Store, then run the one-time local host installer.
- Confirm the popup shows "On-device engine connected."
- Chat normally; press ⌘/Ctrl+M in any supported platform to recall.
Everything the extension captures lives in the same local database the MCP server reads — tell Claude.ai something once, and Claude Code already knows it.
Node SDK (Library)
When you're building a backend service and want to manage agent state persistence programmatically, import the Node SDK client. It performs end-to-end AES-256-GCM encryption client-side and replicates checkpoints to a sync endpoint you choose.
npm install @sovseal/sdk
import { AgentStateClient, CryptoService } from "@sovseal/sdk";
const client = new AgentStateClient({
endpoint: "https://your-project.supabase.co/functions/v1/v2-agent-state",
apiKey: "sov_proj_your_project_uuid",
});
const key = await CryptoService.generateAESKey();
// Client-side AES-GCM encrypted snapshot upload
const receipt = await client.snapshot({
key,
payload: {
agent_id: "agent_a1b2c3",
sequence_number: 0,
parent_snapshot: null,
policy_hash: "0000000000000000000000000000000000000000000000000000000000000000",
timestamp: new Date().toISOString(),
active_context: {
project: "acme-migration",
decisions: ["Postgres over Mongo — team expertise", "Cut scope: no SSO in v1"],
open_question: "Client prefers staged rollout; confirm dates with their ops lead."
}
}
});
// Restore the latest state snapshot
const { receipt: latestReceipt, ciphertextUrl } = await client.restore({
agentId: "agent_a1b2c3",
});
Self-Hosted Edge
The replication endpoint is a Deno edge function — open source, deployable to any Supabase project for full data-residency control.
# From the repo root
supabase functions deploy v2-agent-state
supabase db push # applies the agent_state_snapshots schema
# Point any client at it:
export SOVSEAL_ENDPOINT="https://<your-project>.supabase.co/functions/v1/v2-agent-state"
Source: supabase/functions/v2-agent-state/.
🔗 Integrations & Agent Frameworks
All of these consume the same MCP server through their first-class MCP support. No sovseal-specific adapter is required:
| Framework | How it consumes MCP |
|---|---|
| ElizaOS | @fleek-platform/eliza-plugin-mcp (config-only, stdio or SSE) |
| Hermes Agent | Native MCP, stdio + remote HTTP |
| CrewAI | mcps=[...] field on the agent |
| LangGraph · LangChain | langchain-mcp-adapters (npm + PyPI) |
| Microsoft Agent Framework | Built-in MCP workbench |
| OpenAI Agents SDK | Native MCPServerStdio / MCPServerSse |
| OpenClaw | Native openclaw mcp consumer |
🛠️ MCP Tools Exposed to the LLM
| Tool | Args | Behavior |
|---|---|---|
store_memory |
{ content: string } |
Embed (384-dim, on-device) → write to local LanceDB → return. Ciphertext replication runs write-behind; nothing blocks. |
recall_memory |
{ query: string, topK?: number } |
Embed query (LRU-cached) → vector search local LanceDB → return top-K matches ranked by L2 distance. 0 RTT. |
🔒 Threat Model — Read this before depending on it
We publish exactly what is protected, what isn't yet, and what's on us versus on you. Full detail in SECURITY.md.
Guarantees that hold today:
- Sync confidentiality. AES-256-GCM with a 96-bit random IV per snapshot, encrypted before transmission. The sync server stores ciphertext it cannot read.
- Integrity (VSR). Every recall re-derives
sha256(canonicalize(payload))and compares against the storedclient_payload_hash. Corrupted storage fails closed. - No third-party processing. Embeddings are computed on-device by a version-pinned, hash-verified model. Your text is never sent to an embedding or extraction API.
- Authentication. Bearer token =
sov_proj_<uuid v4>in~/.sovseal/config.json. - Storage. Ciphertext lands in a Supabase Storage bucket. Object paths are SHA-256-derived and unguessable without your
project_id.
Honest status — hardening in flight (v0.3.5):
| Control | Status |
|---|---|
| Zero-knowledge replication (AES-256-GCM + content hashing) | ✅ Shipped |
| On-device, hash-pinned embedding model | ✅ Shipped |
| Identifier sanitization against query-predicate injection | ✅ Shipped |
| Local database encryption at rest | ✅ Shipped v0.3.5 — field-level AES-256-GCM on memory content (embedding vector still in the clear) |
| Master key in OS keychain (HKDF-separated at-rest & sync subkeys) | ✅ Shipped v0.3.5 |
| Programmatic secret redaction before any write | 🔄 Planned — today this is enforced at the prompt level only |
| Model integrity verified strictly before load | ✅ Shipped v0.3.5 — incl. the first-run download path |
As of v0.3.5, memory content is encrypted at rest and the master key lives in the OS keychain, so local filesystem read no longer exposes your memories. Programmatic secret redaction is still prompt-level only — see SECURITY.md. We'd rather tell you that here than have you find out later.
- Key loss (Hobby/Starter/Growth). Lose
~/.sovseal/config.json→ lose every synced snapshot ever made. There is no escrow or recovery flow on these tiers. - Key recovery (Pro/Enterprise). Pro tier adds managed key recovery via Shamir-split escrow custody, and Enterprise adds HSM-backed key recovery.
🤝 Contributing
pnpm install
pnpm --filter @sovseal/mcp-server build
node packages/sovseal-mcp-server/dist/index.js # stdio MCP server
Test (unit + integration + crypto round-trip):
pnpm --filter @sovseal/mcp-server test
pnpm --filter @sovseal/mcp-server run bench-v2
See CONTRIBUTING.md.
🗺️ Roadmap
The core open-source modules — the stdio/SSE MCP server, browser extension, Node SDK, and self-hosted Supabase edge functions — are stable, free, and licensed under Apache 2.0.
Next up, in order:
- v0.3.5 — Security hardening + first intelligence: local at-rest encryption, OS-keychain key custody, code-enforced secret redaction, and the start of typed memory (episodic / semantic / procedural) with reinforcement-aware recall — so sovseal remembers what you've tried, not just what you've said.
- Ambient capture: deterministic session observation for Claude Code and transcript-capable clients — memory that forms without anyone remembering to store it.
- Hosted sync tier — managed, high-availability ciphertext replication for teams that don't want to run their own edge function. (Still zero-knowledge: we host bytes we cannot read.)
- Wallet-key mode (opt-in) — Arweave permanence via Base L2 and Irys, for users who want their encrypted snapshots to outlive any company, including ours. Entirely optional; the core product has no blockchain dependency.
Track progress in CHANGELOG.md and the issue tracker.
📚 Documentation & Support
- Quickstart: see the Quickstart Guide above
- Integrations: see Integrations & Agent Frameworks
- Security: SECURITY.md
- Source:
packages/sovseal-mcp-server/·apps/extension/·supabase/functions/v2-agent-state/ - Release notes:
packages/sovseal-mcp-server/CHANGELOG.md - Issues & PRs: this repository
- Contact: founders@sovseal.com
⚖️ License
Apache 2.0 — for the entire public surface (MCP server, extension, SDK, core protocol, edge function, docs). Fork it, ship it, run it however you like.
Pertanyaan tentang sovseal-memory MCP
Bagaimana cara menambahkan sovseal-memory MCP ke Claude Code?
Jalankan claude mcp add core -- npx -y @sovseal/mcp-server di terminal Anda. Tambahkan --scope user agar tersedia di semua proyek.
Bagaimana cara menambahkan sovseal-memory MCP ke Cursor?
Buka ~/.cursor/mcp.json dan tambahkan server di bawah mcpServers, menggunakan config Cursor yang ditunjukkan di bagian instalasi di atas.
Tool apa yang disediakan sovseal-memory MCP?
Server ini menyediakan 2 tool, termasuk store_memory, recall_memory.
Bagaimana sovseal menjamin privasi?
Semua proses capture, embedding, dan recall berjalan di perangkat Anda, yang berarti teks biasa (plaintext) tidak pernah meninggalkan mesin Anda. Fitur sinkronisasi opsional menggunakan enkripsi AES-256-GCM sehingga server hanya melihat ciphertext.
Apakah ini berfungsi dengan Claude dan Cursor?
Ya, ini dirancang untuk bekerja dengan Claude Desktop, Cursor, Windsurf, Zed, dan klien lain yang kompatibel dengan MCP.
Bisakah saya menggunakannya secara offline?
Ya, mode local-only dapat berfungsi sepenuhnya secara offline tanpa memerlukan akun.