Citadel

dev.citadeldb由 citadeldb.dev 發布v2.7.0更新於 Oct 24, 2026

Encrypted-first embedded database with vector search and agent memory, exposed as MCP tools

已驗證STDIO僅桌面資料庫知識與記憶

概覽

AI 產生的概覽

Citadel 是本地 MCP 伺服器,為助理提供持久且加密的記憶,並支援向量、關鍵字、時效與重要性的混合檢索。

可以做什麼
檢索與檢視記憶:混合檢索、依類型以游標列舉、依精確 ID 批次取得、圖邊查詢、查詢輪廓與依類型摘要,以及從磁碟重新驗證原子完整性。寫入與維護記憶:儲存單一原子或原子化批次寫入(具冪等性)、原地取代內容、新增或移除具類型的邊、重算鄰居連結與重要性。選擇性遺忘:依策略淘汰、依 ID 遺忘並回傳可驗證的抹除憑證,可選擇原子化抹除衍生原子。
適用情境
適合需要在使用者本機跨工作階段保留長期記憶,且要求靜態加密、語意召回與具類型圖結構的助理。適用於需要儲存、搜尋、驗證並選擇性遺忘事實的代理或 IDE 用戶端。
執行需求
以本機 stdio 程序執行,可用 uvx 啟動,或透過 pip、cargo 安裝;僅支援桌面用戶端。需設定 CITADEL_KEY 環境變數作為資料庫通關密語,指定資料庫路徑,並在每次啟動時選擇嵌入模型。語意召回須先明確拉取模型(建議 e5-large 與 ms-marco-minilm);模型不會自動下載。
安裝前請注意
CITADEL_KEY 中的通關密語用於解鎖加密資料庫,請妥善保護密語及存放它的用戶端設定。工具會寫入、更新、建立連結並抹除記憶;遺忘不可復原,且抹除不會撤銷明文匯出或早先備份、快照中保留的金鑰。明文區域模式會關閉逐原子加密與加密抹除。自訂模型目錄會繞過受管快取的驗證。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Citadel,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

citadeldb-mcp

mcp-name: dev.citadeldb/mcp

Model Context Protocol (MCP) server for the Citadel encrypted memory engine. Gives any MCP client (Claude Desktop, an IDE, an agent) persistent, encrypted memory.

Memory lives in a local citadeldb-mem region: AES-256 encrypted at rest, per-atom sealed and HMAC-authenticated, recalled through a hybrid vector + keyword + recency + importance fusion over a PRISM approximate nearest-neighbor index, connected by a typed edge graph, and forgotten by destroying keys (cryptographic erasure).

Install

Run it with no install. For semantic recall, pull the recommended embedder and cross-encoder reranker once, then enable both:

sh
uvx citadeldb-mcp pull e5-largeuvx citadeldb-mcp pull ms-marco-minilm

The pull commands do not open a vault. Before serving, set CITADEL_KEY to the vault passphrase (export CITADEL_KEY="your-passphrase" on macOS/Linux or $env:CITADEL_KEY = "your-passphrase" in PowerShell), then run:

sh
uvx citadeldb-mcp --db memory.cdl --embedder e5-large --reranker ms-marco-minilm

e5-large + ms-marco-minilm is the recommended semantic-recall setup. See the memory benchmarks for measured configurations. Models are never downloaded automatically.

Built-in pulls use release-pinned Hugging Face revisions. Each complete snapshot is verified against compiled sizes and SHA-256 digests, then stored with a BLAKE3 manifest under <models-dir>/<name>/<revision>/. A flat cache created by an earlier CitadelDB release is not trusted; run pull again to create the pinned snapshot. --model-dir and --reranker-dir remain explicit bring-your-own-artifact paths and bypass the managed-cache manifest. Citadel treats those directories as user-trusted and does not attest their contents.

Or install the command with pip install citadeldb-mcp or cargo install citadeldb-mcp, then wire it into Claude Desktop (claude_desktop_config.json):

json
{  "mcpServers": {    "citadel": {      "command": "citadeldb-mcp",      "args": ["--db", "/absolute/path/to/memory.cdl", "--embedder", "e5-large", "--reranker", "ms-marco-minilm"],      "env": { "CITADEL_KEY": "your-passphrase" }    }  }}

The server supports stateless MCP 2026-07-28 discovery and per-request metadata, plus the initialize-based 2025-11-25 and 2025-06-18 revisions for existing clients.

Tools (over a bounded, cancellable JSON-RPC 2.0 stdio transport):

  • mem_recall - hybrid retrieval (vector + keyword + recency + importance); filter by kind/payload, expand along the memory graph, override fusion weights, and optionally attach provenance (derived_from), per-hit integrity verdicts (attest), and resource_links to each hit
  • mem_fetch - deterministic cursor-based listing of a kind (no embedding)
  • mem_get - bounded exact-id batch retrieval in request order, with missing atoms marked explicitly
  • mem_edges - cursor-based typed graph introspection
  • mem_profile - what the memory knows about a query: recall plus its graph neighborhood
  • mem_summarize - per-kind digest of a region
  • mem_verify - re-authenticate atoms off disk: per-atom integrity verdict (authentic / tampered / key_erased / missing / plaintext_unattested)
  • mem_remember - store one atom with optional provenance and retry-safe idempotency
  • mem_remember_batch - atomically store an ordered batch; every entry carries a distinct idempotency key, and a changed reuse rejects the whole batch
  • mem_update - replace a stored atom's payload in place (preserves id, edges, and embedding)
  • mem_link / mem_unlink - add or remove one exact typed edge
  • mem_evolve - recompute an atom's neighbor links and stored importance
  • mem_evict - selective forgetting by policy (cryptographic erasure on encrypted regions)
  • mem_forget - forget atoms by id and return a verifiable erasure receipt; optionally erase their region-local derived_from closure atomically (cryptographic erasure on encrypted regions; immutable atoms require the protected-erasure opt-in)

The citadeldb-mcp binary reads the passphrase from CITADEL_KEY and serves one region (encrypted by default); only protocol messages go to stdout, diagnostics to stderr. --region-mode plaintext disables per-atom encryption and cryptographic erasure for that region; the database remains encrypted at rest. Erasure does not revoke plaintext exports or keys retained in pre-erasure backups or snapshots.

Every server invocation must select an embedder. The CPU Candle embedder is compiled into the standalone server's default build, including the citadeldb-mcp Python package; it is not included in the default citadeldb library wheel. Models are fetched only on explicit pull.

Embedder pull names: e5-large (recommended), e5-large-v2, bge-small, bge-base, bge-large, minilm. Reranker: ms-marco-minilm. Or point --model-dir at a compatible local checkpoint for the selected catalog pipeline, and build with --features cuda-embed to run on an NVIDIA GPU.

This crate is part of the Citadel workspace.

License

Apache-2.0

來源:crates/citadel-mcp/README.md,提交 fa786b2

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

4
  1. v2.7.0最新Sep 28, 2026
  2. v2.6.1Sep 25, 2026
  3. v2.6.0Sep 24, 2026
  4. v2.5.0Sep 16, 2026

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