原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

GraphyLoop

作者:chadixearth版本 0.6.5i★ –i在你的电脑上运行
注册名称io.github.chadixearth/graphyloop

安装

概览

作者提供的说明(英文原文)

Workflow planner, wave dispatcher, persistent swarm memory, and deploy preflight for AI agents.

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。

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

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

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": {
    "graphyloop": {
      "command": "npx",
      "args": [
        "-y",
        "graphyloop",
        "mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add graphyloop -- npx -y graphyloop 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": {
    "graphyloop": {
      "command": "npx",
      "args": [
        "-y",
        "graphyloop",
        "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": {
    "graphyloop": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "graphyloop",
        "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 chadixearth 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 7249 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7249 个服务器的 87% 更新
  • 基础检查结果等于或优于此分类中其他 7249 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

GraphyLoop 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(0.6.5)于5天前进入注册中心。

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 Node.js。

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今天更新
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★ 48,148MIT20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。

GraphyLoop

GraphyLoop is a one-command agentic workflow kit for AI coding agents: it wires Claude Code, OpenCode, Codex, Cursor, Gemini CLI, Oh My Pi and DeepSeek Harness with Workflow v3 (inline-first, one parallel wave, proof before done), a 25-agent squad, persistent memory, Agent Skills and an MCP server. It also ships as a Claude Code plugin and an MCP Registry server. Zero dependencies.

Landing page · npm · Harness guide · Reference · llms.txt

Quick Start

Pick one of three install channels:

1. npx installer (all 7 harnesses)
npx graphyloop        # a bare command installs — it wires every harness it detects

restart your harness, open a real project, then ask your agent:

/chadi-init

Requires Node.js ≥ 20. On a fresh machine with no harness yet, GraphyLoop wires all seven so you are ready whichever one you open first. Target specific ones with --harness claude,omp. Nothing is written into your workspace — everything lives in your home config (~/.graphyloop/ plus each harness's own directory).

2. Claude Code plugin marketplace

Inside Claude Code:

/plugin marketplace add chadixearth/graphyloop

/plugin install graphyloop@graphyloop

then start the workflow with:

/graphyloop:chadi-init

The marketplace manifest is .claude-plugin/marketplace.json and the plugin lives at integrations/claude-code/ (15 /graphyloop:chadi-* commands, 26 agents, 3 core skills, and the graphyloop MCP server). Use the plugin OR `npx graphyloop --harness claude` for Claude Code, not both (installing both registers duplicate tools and agents).

3. MCP Registry

Server name: `io.github.chadixearth/graphyloop` (server.json). Any MCP client that resolves from the official MCP Registry runs the graphyloop npm package over stdio via:

npx -y graphyloop mcp
Supported harnesses
Harness--harnessDetected whenHow GraphyLoop wires itStart the workflow
OpenCodeopencode~/.config/opencode/plugin (graphyloop_* tools) + 26 agents + 15 /chadi-* commands + AGENTS.md/chadi-init
Claude Codeclaude~/.claude/ or ~/.claude.jsonMCP server + 26 agents + 15 commands + ~/.claude/rules/graphyloop-workflow.md (or install the Claude Code plugin instead)/chadi-init (plugin: /graphyloop:chadi-init)
Codexcodex~/.codex/MCP server + 15 prompts + bundled skills in ~/.agents/skills/ + AGENTS.md/prompts:chadi-init
Cursor / Windsurfcursor~/.cursor/MCP server + bundled skills in ~/.agents/skills/ (workflow loads from graphyloop-workflow skill; project init writes /AGENTS.md)ask: "run the graphyloop workflow init"
DeepSeek Harnessdsh~/.dsh/ or $DSH_HOMEMCP server + 26 role prompts + graphyloop-squad skill + AGENTS.mdload the graphyloop-squad skill
Oh My Piomp~/.omp/MCP server in ~/.omp/agent/mcp.json + 26 squad agents + skills; AGENTS.md only if you have noneask: "run the graphyloop workflow init"
Gemini CLIgemini~/.gemini/MCP server in ~/.gemini/settings.json + /chadi-* TOML commands + bundled skills in ~/.gemini/skills/; GEMINI.md only if you have none/chadi-init

Per-harness file locations, verification, dsh notes, and the Gemini CLI sign-in change (personal Google sign-ins stopped working on June 18, 2026; an API key still works): docs/harnesses.md.

Setup with any AI assistant (copy-paste)

Paste the block below into your AI harness — it installs, verifies (GRAPH_LOOP_DOCTOR_OK), and reports on its own. Raw copy: docs/SETUP-PROMPT.md.

You are setting up GraphyLoop (github.com/chadixearth/graphyloop, npm package `graphyloop`) — a one-command agentic workflow kit for AI coding agents: a 25-agent squad, parallel wave planning, persistent memory, a harness-neutral workflow and an MCP server that works in any harness. Zero dependencies.

Goal: install it for THIS machine's harness(es), verify the install actually works, and report. Do NOT edit any config file by hand — run only the installer. Do NOT run npm publish, npm login, or anything unrelated.

Steps:

  1. Prerequisites:
  • Run node --version — must be 20 or newer. If older, tell the user to install Node.js 20+ and stop there.
  • Detect which harnesses exist on this machine (check for any of): ~/.config/opencode/ (OpenCode), ~/.claude.json or ~/.claude/ (Claude Code), ~/.codex/ (Codex), ~/.cursor/ (Cursor / Windsurf), ~/.dsh/ or $DSH_HOME (DeepSeek Harness / dsh), ~/.omp/ (Oh My Pi / omp), ~/.gemini/ (Gemini CLI). On Windows, ~ = %USERPROFILE%.
  1. Install:
  • Run: npx --yes graphyloop (a bare graphyloop is the install command: it wires every detected harness, or all 7 on a fresh machine.)
  • To target specific harnesses: npx --yes graphyloop --harness claude,omp (names: opencode, claude, codex, cursor, dsh, omp, gemini)
  • Optional Claude Code plugin path (use the plugin OR npx graphyloop --harness claude, not both): inside Claude Code run /plugin marketplace add chadixearth/graphyloop then /plugin install graphyloop@graphyloop.
  • If npx asks "Ok to proceed?", answer yes. If npx is missing, stop and tell the user to install Node.js 20+ (npx ships with npm).
  1. Verify — every applicable check must pass:
  • npx --yes graphyloop doctor prints one row per harness (present / wired) and its LAST line must be GRAPH_LOOP_DOCTOR_OK. If it prints GRAPH_LOOP_DOCTOR_ISSUES , run the fix: command it shows for each unwired row, then run doctor again.
  • Core engine files exist: ~/.graphyloop/graphyloop/cli.mjs , ~/.graphyloop/mcp-server.mjs , ~/.graphyloop/lib/mcp.mjs , ~/.graphyloop/lib/engine.mjs .
  • OpenCode (if present): ~/.config/opencode/opencode.json contains plugin entries "./plugins/graphyloop/plugin.js" and "./plugins/server-guard/plugin.js", and ~/.config/opencode/agents/ contains 26 .md files.
  • Claude Code (if present): ~/.claude.json has an mcpServers.graphyloop entry, ~/.claude/rules/graphyloop-workflow.md exists, and ~/.claude/agents/ is populated (unless using the Claude Code plugin instead).
  • Codex (if present): ~/.codex/config.toml contains a [mcp_servers.graphyloop] section, and ~/.agents/skills/graphyloop-workflow/SKILL.md exists.
  • Cursor (if present): ~/.cursor/mcp.json has a "graphyloop" entry, and ~/.agents/skills/graphyloop-workflow/SKILL.md exists (Cursor uses no home rules file; the workflow loads from ~/.agents/skills/graphyloop-workflow).
  • DeepSeek Harness (if present): ~/.dsh/cordis.patch.yml contains a row id: graphyloop-mcp naming '@deepseek-ai/dsh-mcp-client', ~/.dsh/AGENTS.md exists, and ~/.dsh/skills/ holds graphyloop-squad. Optional deeper check: dsh --profile headless --dump-config prints that row. In dsh the tools are namespaced — call them as mcpgraphyloop (e.g. mcpgraphyloopswarm_state).
  • Oh My Pi (if present): ~/.omp/agent/mcp.json has mcpServers.graphyloop, and ~/.omp/agent/agents/ holds the squad .md files. An existing ~/.omp/agent/AGENTS.md is intentionally kept — the workflow then loads from the bundled skill graphyloop-workflow.
  • Gemini CLI (if present): ~/.gemini/settings.json has mcpServers.graphyloop, ~/.gemini/commands/chadi-init.toml exists, and graphyloop-workflow/SKILL.md exists in ~/.gemini/skills/ (or ~/.agents/skills/ when Codex/Cursor is also installed). An existing ~/.gemini/GEMINI.md is intentionally kept.
  • If any check fails: re-run the install with --force (automatic backups) and re-verify. Still failing? Report the exact error and stop.
  1. Wrap up: tell the user to RESTART their harness (close/reopen the terminal or editor), open a real project (not their home directory), and start the workflow: ask for /chadi-init (OpenCode, Claude Code, Gemini CLI — or /graphyloop:chadi-init with the Claude Code plugin), /prompts:chadi-init (Codex), or "run the graphyloop workflow init" (Oh My Pi, Cursor, Windsurf). In the DeepSeek Harness there are no slash commands: ask the agent to load the graphyloop-squad skill instead. Give a one-line summary of what was installed.

Do not ask permission for reversible steps — proceed. Stop only for: Node < 20, an install failure, or a prompt you cannot answer.

How the workflow works

Workflow v3 is harness-neutral: the same 12 rules run in OpenCode, Claude Code, Codex, Cursor, Windsurf, DeepSeek Harness, Oh My Pi and Gemini CLI.

flowchart LR

A[Recall memory_search] --> G0[Goal + proof state what & check] G0 --> B{Size the work} B -- "inline ≤ 8 known files" --> I[Inline edit any mix of layers] B -- "2+ independent slices (~5+ min each)" --> C[ctx pack + contract ctx-slug.md + contract-slug.md] C --> D[One wave 1–3 lanes, driver keeps a slice] D --> E[Proof, not claims run it, real browser / URL] I --> E E --> F[Report Changed / Files / Verified / Skills / Blocked] F --> G[Record memory_store + why & commit/PR]

  1. Recall first, record last — memory_search before planning; memory_store one dense line after, including the *why* and the commit/PR it landed in.
  2. Goal + proof up front — state the end state, the measurable check that proves it, and the invariant it must not break ("prompt the what, not the how"; never weaken a test to make it pass).
  3. Inline first (measured) — up to 8 known files in any mix of layers, when the code is known or mappable in one batched read pass; a dispatch costs the driver minutes of waiting while an inline edit costs seconds.
  4. Fan out only for 2+ independent slices of about 5+ minutes each — 1–3 lanes (max 4), strictly disjoint files; the driver keeps the largest or most coupled slice and builds it while lanes run.
  5. Context pack before dispatch — write ctx- .md (path:line, current code, pattern to copy) so lanes start editing instead of rediscovering.
  6. Freeze the contract — contract- .md is the only cross-lane dependency.
  7. Turn economy — batch reads, first edit by turn 5, done in about 20 turns (40+ = mis-sized).
  8. Isolate what collides — a lane that runs servers, databases or browsers gets its own wor

只显示了开头部分;其余内容请在仓库中阅读

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