MemoCat — Shared AI Memory

io.github.MontyGovernance由 GitHub 帳號 MontyGovernance 發布v0.4.3更新於 Oct 24, 2026

One shared, persistent memory across AI agents and systems, with semantic recall and live updates.

發布方自己的服務:Memory.fit

已驗證STDIO僅桌面資料庫知識與記憶

概覽

AI 產生的概覽

自架設的 MCP 伺服器,為 AI 代理提供一份共用的持久記憶,支援語意、關鍵字與混合檢索,可跨工作階段與用戶端使用。

可以做什麼
在具名作用域與鍵空間中單筆或批次儲存、更新與遺忘記憶,結構化寫入或篩選檢索前可檢查欄位結構。依語意、精確關鍵字、混合檢索、精確鍵或中繼資料召回記憶,並列出已存記憶。等待其他代理寫入到達,不需輪詢。建立、列出與移除鍵空間,並調整快取容量。執行語意索引、快照與政策等管理工具。
適用情境
當多個 MCP 用戶端或代理需要共用跨工作階段保留的決策、偏好與專案脈絡,且希望記憶留在本機而非託管服務時使用。
執行需求
透過 stdio 在本機執行;可用 Claude Desktop 安裝包、Claude Code 外掛,或以 uvx 安裝(需 Python 3.10+)。會自動啟動本機 Montycat 引擎,也可用 MONTYCAT_URI 指向自行執行的引擎(例如以 Docker)。另有 TLS、預設鍵空間與作用域等選用變數。
安裝前請注意
MONTYCAT_URI 連線字串可能包含引擎憑證,不要放進共用設定。作用域只是命名空間,不是安全邊界;需要真正隔離時應為每個伺服器使用最小權限的獨立憑證。遺忘與移除鍵空間等破壞性工具已宣告,用戶端會跳出確認。僅設定 MONTYCAT_TLS=true 時連線雖加密但不驗證,除非另行設定驗證。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 MemoCat — Shared AI Memory,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

[Montycat logo]

Montycat MCP - Shared Memory for AI Agents

A self-hosted MCP server that gives AI agents persistent, searchable memory. Claude, Codex, Cursor, and any Model Context Protocol client write to one memory and read each other's.

[PyPI] [Python] [License]

  • Memory that survives the chat. Decisions, preferences, and project context carry into the next session.
  • One memory, many agents. Every MCP client you use works from the same facts.
  • Recall by meaning, keyword, or both. Vector search finds a memory when the wording differs, BM25 nails exact identifiers, and hybrid mode fuses the two. Exact-key and metadata lookup too.
  • Yours. Server, engine, and embeddings run on your machine. No hosted memory service, no cloud embedding API.

Install

Claude Desktop — download montycat-mcp.mcpb and drag it into Claude Desktop. No Python needed. That link always serves the current release; every release also carries a version-named copy and a .sha256 to check it against.

Claude Code — install uv, then:

text
/plugin marketplace add MontyGovernance/montycat-mcp/plugin install montycat-mcp@montygovernance

/mcp confirms the montycat server is connected.

Codex, Cursor, other MCP clients — point your client's stdio config at uvx montycat-mcp (Python 3.10+). For Codex:

bash
codex mcp add montycat -- uvx montycat-mcp

The engine

Memory lives in a Montycat Semantic engine. Montycat MCP starts a local one for you, so most people can stop reading here.

Point it at an engine you already run:

bash
export MONTYCAT_URI="montycat://memory-agent:password@localhost:21210/memories"export MONTYCAT_TLS=true   # remote engines only

Or start one yourself with Docker:

bash
docker run -d --name montycat -p 21210:21210 -p 21211:21211 \  -e MONTYCAT_SUPEROWNER=admin -e MONTYCAT_PASSWORD=change-me \  -v montycat_data:/var/lib/.montycat \  montygovernance/montycat:semantic

On Apple Silicon use the arm64-semantic tag instead — semantic is the amd64 image, and it crashes under emulation. Port 21211 carries live memory watches.

Use it

Talk to your agent normally; it picks the tool.

Remember that the team chose PostgreSQL for the billing service.

What did we decide about the billing database?

Save this to the shared engineering scope.

scope decides where a memory lives — alice for private, engineering for a team, shared for common. It is a namespace, not a security boundary: for real isolation, give each MCP server its own least-privilege Montycat credential.

Tools

NeedTools
Storemontycat_remember, montycat_remember_bulk, montycat_update, montycat_forget
Recallmontycat_semantic_search, montycat_recall, montycat_list_memories
Inspect schemasmontycat_list_enforced_schemas — check field names and data types before structured writes or filtered retrieval
Collaboratemontycat_await_memory_change — wait for another agent's write, no polling
Namespacesmontycat_list_keyspaces, montycat_create_keyspace, montycat_update_cache, montycat_remove_keyspace
Adminsemantic index, snapshot, and policy tools — see the plugin guide

For persistent namespaces, cache is a capacity in MB and compression is chosen by montycat_create_keyspace. Compression cannot be changed after the keyspace is created; migrate into a new keyspace to use a different setting. Cache capacity can be changed later with montycat_update_cache.

Destructive tools are declared as such, so your client's confirmation prompts apply.

Configuration

VariablePurpose
MONTYCAT_URIConnection string: montycat://user:password@host:port/store
MONTYCAT_TLStrue for a remote TLS engine
MONTYCAT_TLS_VERIFYOptional: true to verify with the platform trust store
MONTYCAT_TLS_CERTIFICATE_PATHOptional PEM certificate path for exact certificate pinning
MONTYCAT_TLS_CERTIFICATE_FINGERPRINTOptional SHA-256 certificate fingerprint as an alternative pin

All three verification settings are optional. With only MONTYCAT_TLS=true, MCP retains the historical encrypted-but-unverified behavior; with TLS unset or false, existing plaintext configurations are unchanged. | MONTYCAT_DEFAULT_KEYSPACE | Memory namespace; memory by default | | MONTYCAT_SCOPE | Default scope when a call omits one | | MONTYCAT_AUTO_PROVISION | Create a permitted scope on first use; true by default | | MONTYCAT_AUTOSTART | off to require an already-running engine |

Compose setup and the full variable list: compose.yaml and the plugin guide.

More

Changelog · Privacy · Issues · Docs · Docker Hub

Existing MemoCat installs keep working: memocat-mcp, MEMOCAT_*, and memocat:// are still supported. New setups should use the Montycat names.

MIT

來源:README.md,提交 c904d61

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

1
  1. v0.4.3最新Sep 16, 2026

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