Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Job search and interview prep MCP. 15 tools, OAuth 2.1, cross-LLM. four-leaf.ai.
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 …”。
适用于网页版、桌面版和手机版 Claude:
https://four-leaf.ai/api/mcp在终端中运行这条命令
claude mcp add --transport http clover-public https://four-leaf.ai/api/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"clover-public": {
"url": "https://four-leaf.ai/api/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": {
"clover-public": {
"type": "http",
"url": "https://four-leaf.ai/api/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。
ChatGPT 只能连接互联网上的服务器:
https://four-leaf.ai/api/mcp菜单名称可能因套餐和版本不同而略有差异。
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。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
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 fourleafai 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
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
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。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.1.0)于2个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
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。
An open-source Skill that turns Claude (or ChatGPT, Cursor, Codex, GitHub Copilot) into a job search and interview prep coach. It pulls real job postings, role-specific interview intelligence, rubric-scored feedback on practice answers, and resume scoring from the hosted Four-Leaf MCP, then walks the user through preparing for an actual interview.
Free to install and use, including scoring the answers you type. Voice mock interviews (spoken answers, adaptive follow-ups) and full AI resume tailoring live on four-leaf.ai; the Skill surfaces those as an upgrade path when they're the right next step.
Walks a user through prep for a specific role at a specific company. The Skill greets, asks what they're prepping for, and routes them into one of seven guided workflows. Every workflow pulls live data from the Four-Leaf MCP's fifteen tools (jobs and full postings, role intel, question bank, answer scoring, match scoring, comp research, application tracker) and adds the Skill's coaching on top.
You don't type these as commands. Say what you want in plain language and the coach routes to the right workflow:
Two steps. The Skill tells your AI tool how to coach. The hosted MCP gives the Skill live data.
npx four-leaf-coach add
That's it. The CLI detects your tool (Claude Code, Cursor, Codex, or GitHub Copilot), asks for scope when it matters, and copies the right bundle into the right place. Useful flags:
--tool pick the tool yourself: claude-code, cursor, codex, or github-copilot--scope Claude Code only; where to install--dry-run show what it would do without writing anything--yes skip confirmation prompts, --force overwrite an existing installfour-leaf-coach list show the supported tools and what's detected in the current directoryCursor needs the Nightly channel with Settings, Rules, Agent Skills enabled. The other tools work out of the box.
The Skill works in degraded mode (coaching only, no live job data) without the MCP. To get real job search, role intel, answer scoring, and resume scoring, install the hosted MCP:
# Claude Code, Claude Desktop, and any tool that uses claude-mcp config
claude mcp add --transport http four-leaf https://four-leaf.ai/api/mcp
The first tool call opens the browser for OAuth. A free Four-Leaf account works (3-day trial included, no credit card).
For Cursor, ChatGPT Desktop, and other MCP-aware tools, configure the same URL (https://four-leaf.ai/api/mcp) per that tool's MCP setup docs.
Once it's installed, just tell the coach what you need in plain language. Say something like "help me prep for a senior software engineer interview at Google" and it takes it from there. There are no subcommands to memorize; the coach routes based on what you ask. (In Claude Code you can also invoke it explicitly with /four-leaf-coach.)
If you'd rather not run npx (air-gapped network, or you just want to see what lands where), clone and build the bundles yourself. This is exactly what npx four-leaf-coach add --tool automates.
git clone https://github.com/fourleafai/clover-public.git
cd clover-public npm run build
npm run build reads skills/four-leaf-coach/SKILL.md plus the adjacent references/ tree and writes a dist/ / directory for each supported tool. Then copy your tool's bundle into place:
| Tool | Build output | Copy into place |
|---|---|---|
| Claude Code (global, all projects) | dist/claude-code/ | cp -r dist/claude-code/.claude ~/ |
| Claude Code (single project) | dist/claude-code/ | cp -r dist/claude-code/.claude PROJECT/ (replace PROJECT with your project path) |
| Cursor (Nightly + Agent Skills enabled) | dist/cursor/ | cp -r dist/cursor/.cursor PROJECT/ |
| OpenAI Codex CLI | dist/codex/ | cp -r dist/codex/AGENTS.md dist/codex/references PROJECT/, then run Codex from PROJECT |
| GitHub Copilot | dist/github/ | cp -r dist/github/.github PROJECT/ (flattened single-file variant) |
The GitHub Copilot bundle is a single flattened file (.github/copilot-instructions.md) because Copilot reads one instructions file and doesn't follow references. The build inlines the whole Skill for it. The other three tools follow file references, so they get the source tree as-is.
The Skill surfaces these when they're the right next step. It doesn't push.
What is four-leaf-coach? An open-source Skill that turns Claude, Cursor, OpenAI Codex, or GitHub Copilot into a job-search and interview-prep coach. The Skill is a structured set of instructions plus reference files that your AI tool loads. It works with the hosted Four-Leaf MCP server for live data (real job postings, role-specific interview intelligence, answer scoring, resume scoring, your application tracker).
How is this different from just prompting Claude for interview prep? Generic prompts produce generic advice. four-leaf-coach calls real tools: search_jobs returns actual apply URLs from 140,000+ active postings and get_job expands one to the full text; match_score runs a real scoring algorithm against your resume; generate_practice_questions produces role-calibrated questions and score_answer grades what you type against a five-dimension rubric; save_application puts a role in your tracker. The Skill orchestrates the calls and coaches around them.
Do I need a Four-Leaf account? For the data tools (jobs, role intel, question bank, answer scoring, match scoring, comp research, application tracker) a free Four-Leaf account works. The 3-day trial requires no credit card. Voice mock interviews and full AI resume tailoring are paid features on four-leaf.ai. The Skill surfaces those as an upgrade path when relevant.
Does the MCP work with ChatGPT? Yes. The MCP is HTTP-based with OAuth, so any MCP-aware client connects: Claude Desktop, Claude Code, Cursor, ChatGPT Desktop (Plus + Dev mode), Cline, Continue, Windsurf. The Skill itself is a Claude / Cursor / Codex / Copilot primitive; ChatGPT doesn't yet have a comparable file-based Skill convention, but the underlying MCP tools work there.
Can I use the Skill without the MCP? Yes, in degraded mode. Without the MCP, the Skill still coaches with structured workflows for prep, practice, JD analysis, and negotiation, just without live job listings, rubric-scored answers, or real resume scoring. Install the MCP to unlock the live data path.
Is the question bank really open? The Skill, the per-tool dist pipeline, and the install CLI are MIT-licensed in this repo. The question bank itself lives behind the MCP today; the open-data play is on the roadmap.
What about Pi, Gemini CLI, OpenCode, Trae, Rovo Dev, Qoder? On the roadmap. The dist pipeline can target any AI tool with a documented Skill or instructions-file convention. PRs welcome.
README.md you are here
LICENSE MIT package.json CLI + build wiring, npm metadata bin/ four-leaf-coach.js the npx four-leaf-coach add CLI scripts/ build.js generates dist/ / bundles from the source below .claude-plugin/ plugin.json manifest for Claude Code plugin marketplace .mcp.json auto-wires the hosted Four-Leaf MCP on plugin install skills/ four-leaf-coach/ SKILL.md entry point your AI tool loads (source of truth) references/ mcp-tools.md reference for the MCP tools upgrade-flow.md paid-tier handling pattern commands/ per-workflow instructions kickoff.md find-jobs.md prep-role.md practice.md analyze-jd.md negotiate-prep.md interview-strategy.md dist/ generated by npm run build (gitignored, not committed)
skills/four-leaf-coach/ is the source of truth. dist/ is generated output, so edit the source and rerun npm run build.
Done so far: per-tool dist/ bundles generated from a single source (npm run build), a flattened single-file variant for GitHub Copilot, and the npx four-leaf-coach add one-command installer.
PRs welcome that improve a command's coaching, add a new command, or fix a voice issue. Anything that drifts the Skill's positioning away from "coach, not cheat tool" will be declined.
MIT. See LICENSE.