Global Agent Memory

Name: Global Agent Memory
Author: ozankasikci

作者：ozankasikci版本 0.1.6i★ –i在你的电脑上运行

注册名称io.github.ozankasikci/global-agent-memory

安装

概览

作者提供的说明（英文原文）

Shared, project-aware memory for Claude Code, Codex, and other agents with human review.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i尚未统计★ –

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在你的电脑上运行
传输方式: stdio
分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：1 项中通过 1 项
在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
注册中心没有列出需要填写的密钥。

你需要

PyPI已安装 Python 的 uv（用于 uvx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "global-agent-memory": {
      "command": "uvx",
      "args": [
        "global-memory-mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add global-agent-memory -- uvx global-memory-mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "global-agent-memory": {
      "command": "uvx",
      "args": [
        "global-memory-mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "global-agent-memory": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "global-memory-mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上，无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 ozankasikci 验证，该账户拥有此仓库
… 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
– 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
– 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
… 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

星标数多于此分类中其他 7283 个服务器的 0%
发布到注册中心的时间比此分类中其他 7283 个服务器的 22% 更新
基础检查结果等于或优于此分类中其他 7283 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

Global Agent Memory 安全吗？

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

注册中心没有列出必需的密钥，不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端？

它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（0.1.6）于4个月前进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它？

同一分类中有：Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

作者：upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT昨天更新

安装

Codebase Memory

作者：DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT21天前更新

安装

Exa

作者：exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Global Agent Memory

Local-first, project-aware, durable memory for Claude Code, Codex, and other

MCP-compatible agents.

Global Agent Memory gives multiple coding agents one shared, reviewable memory without handing control of your knowledge base to a hosted service. Markdown files are canonical, a hybrid local MCP runtime is the public agent interface, and the dashboard lets a human approve, edit, protect, or remove what agents remember. Agent commands work without a background server. The authenticated localhost server starts on demand for the dashboard and can optionally run continuously for live file watching and shared embedding work.

One Vault. Multiple agents. Human-controlled memory.

Quick start · Obsidian Vault · Dashboard · How it works · Security · MCP contract · Documentation

Why Global Agent Memory?

Coding agents are useful inside a session, but important context is often lost between sessions or fragmented across individual clients. Global Agent Memory provides a durable layer for knowledge such as:

architectural decisions and project conventions;
verified workflows and operational runbooks;
recurring problems and their proven solutions;
project preferences, entities, and handoff summaries;
bounded context for a new task or agent session.

Agents propose memories as candidates. A human reviews them before they become durable, controls their visibility, and can later update, supersede, archive, or hard-delete them.

How it compares

Approach	Shared across agents	Human-reviewable	Project-aware	Owner-controlled access	Portable source of truth
`CLAUDE.md` / `AGENTS.md`	Limited	✓	✓	—	✓
Basic memory MCP	✓	Varies	Varies	Varies	Varies
Hosted agent memory	✓	Varies	✓	Provider-defined	—
Global Agent Memory	✓	✓	✓	✓	Markdown

Use project instruction files for compact rules that always belong in a prompt. Use Global Agent Memory when knowledge should be searchable, shared between clients, reviewed by a person, updated over time, or hidden behind explicit permission.

Highlights

Shared across agents — Claude Code, Codex, and other MCP clients use the same service and immutable memory IDs.
Project-aware by default — Git roots, remotes, aliases, and the project registry keep retrieval scoped to the active project.
Markdown is canonical — the Vault remains readable, portable, backup-friendly, and usable with Obsidian.
Human review workflow — agents create candidates; owners approve, edit, reject, or resolve conflicts in the dashboard.
Protected and sealed memory — sensitive knowledge can be excluded from ordinary retrieval and placed behind owner-controlled access.
Hybrid local search — SQLite FTS5 provides keyword retrieval; optional Ollama embeddings and sqlite-vec add semantic ranking.
Offline-friendly — keyword search and lifecycle operations continue when Ollama is unavailable.
Rebuildable generated state — SQLite, FTS, vectors, queues, and caches can be recreated from Markdown.
Frozen MCP V1 contract — tools, resources, prompts, envelopes, and compatibility rules are versioned in the repository.
No required background server: Claude Code, Codex, and CLI commands fall back to the same MCP application services in-process when the optional daemon is offline.
Local security boundary: when the dashboard or HTTP MCP is active, the server binds to 127.0.0.1 and requires a generated bearer token stored outside the Vault.

Built for real project vaults

The opt-in performance suite creates 10,000 synthetic memories and exercises the same indexing and retrieval paths used by both runtime modes. On the recorded macOS ARM64 baseline, a full rebuild takes 36.5 seconds, warm keyword search P95 is 56 ms, warm hybrid search P95 is 76 ms, and incremental stdio proxy overhead is 1.5 ms. Results vary by machine; the changed-note, search, and proxy budgets run as regression gates. See the methodology and complete baseline.

Three surfaces, one memory system

Global Agent Memory is more than an MCP server. Agents, owners, and knowledge workers use the same canonical memories through three purpose-built surfaces:

Surface	Designed for	What it provides
MCP	Claude Code, Codex, and other agents	Project-aware context, search, candidate creation, safe updates, lifecycle actions, and permission requests through a frozen V1 contract
Obsidian Vault	Reading, writing, linking, and long-term knowledge ownership	Portable Markdown and YAML, templates, native Bases views, project overview hubs, wikilinks, backlinks, graph navigation, and direct-edit synchronization
Local dashboard	Fast owner review and administration	Candidate approval and editing, conflict comparison, visibility classification, protected-access decisions, search, projects, activity, backups, and system health

The Vault is the durable source of truth. The dashboard is a complementary control plane, and the MCP interface is the safe automation layer used by agents. You can use Obsidian, the dashboard, or both without creating separate copies of your memory.

Dashboard at a glance

Real dashboard UI with synthetic Atlas project data. No private Vault content is shown.

Quick start

This is the shortest path to persistent memory for Claude Code, Codex, and other MCP clients. The guided installer creates the local service, Obsidian-compatible Vault, dashboard, MCP registrations, and agent skills together.

Requirements

macOS or Linux
Python 3.12 or newer
uv
Claude Code or Codex for the managed client integrations
Optional: Obsidian for browsing the Markdown Vault
Optional: Ollama for semantic retrieval

1. Install

uv tool install global-memory-mcp

To install the latest unreleased source, use uv tool install git+https://github.com/ozankasikci/global-agent-memory.git. For a local checkout, use uv tool install ..

2. Run guided setup

global-memory setup

Setup shows one plan and asks once before it changes anything. It initializes the local Vault, creates the protected token, detects Claude Code and Codex, installs their MCP integrations and skills, verifies healthy clients, and opens the dashboard. Opening the dashboard starts its authenticated localhost server on demand. The command is idempotent, so running it again repairs or updates managed components without replacing unrelated client configuration.

Use flags when you need a non-default setup:

# Non-interactive installation

global-memory setup --yes

Choose a different Vault on first setup

global-memory setup --vault "$HOME/Memory"

Install only one client, or no client yet

global-memory setup --clients claude-code global-memory setup --clients none

Optional: install an always-on native service for live watching and shared indexing

global-memory setup --service

Preview without changing files or services

global-memory setup --dry-run

3. Use the installed agent shortcuts

Setup installs five basic shortcuts for each detected client:

Shortcut	Purpose
`gam-context`	Load project-aware context for a task
`gam-search`	Find a decision, fact, error, convention, or solution
`gam-remember`	Propose explicitly supplied durable knowledge as a candidate
`gam-review`	Show the candidate queue without changing it
`gam-dashboard`	Open the authenticated dashboard

In Claude Code, invoke them directly, for example /gam-context fix the upload retry bug. In Codex, type /skills and choose one, or mention it directly, for example $gam-context fix the upload retry bug.

4. Open the dashboard again

global-memory dashboard

You can also ask a connected agent:

Open the Global Agent Memory dashboard.

The agent calls memory_dashboard_open and opens the same authenticated local dashboard.

Manual installation and repair

The individual commands remain available for advanced setups and troubleshooting:

global-memory init --vault "$HOME/Documents/Global Agent Memory"

global-memory daemon install-service --kind launchd # use systemd on Linux global-memory integrations install all global-memory integrations verify all global-memory doctor

Using it with an agent

After integration, you normally describe your intent instead of running memory commands manually.

Retrieve context before work

Before you start, load the relevant memory for this project and summarize the

conventions and recent decisions.

Propose a durable memory

Remember that production ARM64 binaries must be built locally and uploaded to the

server. Add it as a project convention with the deployment discussion as evidence.

The agent creates a candidate. Nothing becomes active until it is approved.

Update existing knowledge

Find the deployment memory and update it with the new health-check command. Do not

create a duplicate.

Open the review surface

Open the memory dashboard so I can review the candidates.

The shared integration skill teaches supported agents when to retrieve, propose, update, and avoid duplicating memory.

Obsidian Vault

The configured Obsidian Vault is the human-readable, durable source of truth—not an export of an opaque database. Every managed memory is a normal Markdown file with YAML properties, a stable memory ID, lifecycle metadata, and project-aware links.

Initialization adds an Obsidian workspace without replacing your existing files:

templates for decisions, facts, solutions, conventions, preferences, entities, references, session summaries, and project overviews;
native Bases views for the candidate review queue, active knowledge, recent updates, decisions by project, verified solutions, and lifecycle history;
project overview hubs that embed project memories and remain stable as notes move through candidate, active, rejected, superseded, or archived folders;
wikilinks and reciprocal supersession links for backlinks and graph navigation;
request-time synchronization, so ordinary content and descriptive-property edits made in Obsidian become searchable without a background service;
optional watcher synchron

只显示了开头部分；其余内容请在仓库中阅读

Global Agent Memory

概览

PopNx MCP 的三大支柱

它能帮你做什么

安装

安装之前

它能做什么

基础检查i

作者与仓库一致

仍在维护

有许可证

端点有响应

使用 OAuth 登录

工具描述中没有隐藏指令

与“搜索与 AI 记忆”中的其他服务器比较i

常见问题

替代选择

Context7

Codebase Memory

Exa

作者的 README

Global Agent Memory

Why Global Agent Memory?

How it compares

Highlights

Built for real project vaults

Three surfaces, one memory system

Dashboard at a glance

Quick start

Requirements

1. Install

2. Run guided setup

Choose a different Vault on first setup

Install only one client, or no client yet

Optional: install an always-on native service for live watching and shared indexing

Preview without changing files or services

3. Use the installed agent shortcuts

4. Open the dashboard again

Manual installation and repair

Using it with an agent

Retrieve context before work

Propose a durable memory

Update existing knowledge

Open the review surface

Obsidian Vault