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 (keyword-only recall - works immediately, no downloads):

uvx citadeldb-mcp --db memory.cdl

For the best recall (recommended - this is the benchmark config): pull the semantic embedder and the cross-encoder reranker once, then enable both:

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

e5-large + ms-marco-minilm is the highest-recall setup and the exact config behind the memory benchmark numbers. Models are never downloaded automatically.

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

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

Tools (over a synchronous, hand-rolled 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 listing of a kind (no embedding)
  • mem_edges - 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 / mem_remember_batch - store atoms with payload, importance, TTL, immutability
  • mem_update - replace a stored atom's payload in place (preserves id, edges, and embedding)
  • mem_link - connect atoms with a typed edge
  • mem_evolve - recompute an atom's neighbor links and score
  • mem_evict - selective forgetting by policy (cryptographic erasure on encrypted regions)
  • mem_forget - forget atoms by id and return a verifiable erasure receipt (cryptographic erasure on encrypted regions; skips immutable atoms unless forced)

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.

Recall is keyword-only (a mock embedder) until you enable a semantic model. The (CPU) Candle embedder is compiled into the default build; models are fetched only on explicit pull, never automatically. e5-large + the ms-marco-minilm reranker (shown above) is the recommended, highest-recall setup.

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 local model directory for a fully offline setup, and build with --features cuda-embed to run on an NVIDIA GPU.

This crate is part of the Citadel workspace.

License

Apache-2.0

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Credits

Author: Yuriy Peysakhov

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Python >=3.10

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