MemoCat — Shared AI Memory

io.github.MontyGovernance由 GitHub 账号 MontyGovernance 发布v0.4.3更新于 Oct 24, 2026

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

发布方自己的服务:Memory.fit

已验证STDIO仅桌面数据库知识与记忆

概览

AI 生成的概览

自托管的 MCP 服务器,为 AI 代理提供一份共享的持久记忆,支持语义、关键词和混合检索,跨会话与客户端可用。

可以做什么
在命名作用域和键空间中单条或批量存储、更新和遗忘记忆,结构化写入或过滤检索前可检查字段模式。按语义、精确关键词、混合检索、精确键或元数据召回记忆,并列出已存记忆。等待其他代理写入到达,无需轮询。创建、列出和删除键空间,并调整缓存容量。运行语义索引、快照和策略等管理工具。
适用场景
当多个 MCP 客户端或代理需要共享跨会话保留的决策、偏好和项目上下文,并且希望记忆留在本机而不是托管服务上时使用。
运行要求
通过 stdio 在本机运行;可用 Claude Desktop 安装包、Claude Code 插件,或用 uvx 安装(需 Python 3.10+)。会自动启动本地 Montycat 引擎,也可用 MONTYCAT_URI 指向自行运行的引擎(例如用 Docker)。另有 TLS、默认键空间和作用域等可选变量。
安装前请注意
MONTYCAT_URI 连接串可能包含引擎凭据,不要放进共享配置。作用域只是命名空间,不是安全边界;需要真正隔离时应为每个服务器使用最小权限的独立凭据。遗忘和删除键空间等破坏性工具已声明,客户端会弹出确认。仅设置 MONTYCAT_TLS=true 时连接虽加密但不验证,除非另行配置验证。

安装

在 SourceWeft 中

  1. 打开 控制台中的 MemoCat — Shared AI Memory,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

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

来源:README.md,提交 c904d61

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.4.3最新Sep 16, 2026

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