Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Workflow planner, wave dispatcher, persistent swarm memory, and deploy preflight for AI agents.
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。
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。
选择你使用的 AI 应用,然后复制设置。
你需要
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。
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。
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
注册名称已通过 GitHub 账户 chadixearth 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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。
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。
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)。
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。
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。
同一分类中有:Context7, Codebase Memory, Exa
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
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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 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
Pick one of three install channels:
npx installer (all 7 harnesses)npx graphyloop # a bare command installs — it wires every harness it detects
/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).
Inside Claude Code:
/plugin marketplace add chadixearth/graphyloop
/plugin install graphyloop@graphyloop
/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).
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
| Harness | --harness | Detected when | How GraphyLoop wires it | Start the workflow |
|---|---|---|---|---|
| OpenCode | opencode | ~/.config/opencode/ | plugin (graphyloop_* tools) + 26 agents + 15 /chadi-* commands + AGENTS.md | /chadi-init |
| Claude Code | claude | ~/.claude/ or ~/.claude.json | MCP server + 26 agents + 15 commands + ~/.claude/rules/graphyloop-workflow.md (or install the Claude Code plugin instead) | /chadi-init (plugin: /graphyloop:chadi-init) |
| Codex | codex | ~/.codex/ | MCP server + 15 prompts + bundled skills in ~/.agents/skills/ + AGENTS.md | /prompts:chadi-init |
| Cursor / Windsurf | cursor | ~/.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 Harness | dsh | ~/.dsh/ or $DSH_HOME | MCP server + 26 role prompts + graphyloop-squad skill + AGENTS.md | load the graphyloop-squad skill |
| Oh My Pi | omp | ~/.omp/ | MCP server in ~/.omp/agent/mcp.json + 26 squad agents + skills; AGENTS.md only if you have none | ask: "run the graphyloop workflow init" |
| Gemini CLI | gemini | ~/.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.
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:
node --version — must be 20 or newer. If older, tell the user to install Node.js 20+ and stop there.dsh), ~/.omp/ (Oh My Pi / omp), ~/.gemini/ (Gemini CLI). On Windows, ~ = %USERPROFILE%.graphyloop is the install command: it wires every detected harness, or all 7 on a fresh machine.)npx graphyloop --harness claude, not both): inside Claude Code run /plugin marketplace add chadixearth/graphyloop then /plugin install graphyloop@graphyloop.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.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).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.
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]
memory_search before planning; memory_store one dense line after, including the *why* and the commit/PR it landed in.ctx- .md (path:line, current code, pattern to copy) so lanes start editing instead of rediscovering.contract- .md is the only cross-lane dependency.只显示了开头部分;其余内容请在仓库中阅读