Clover Public

io.github.fourleafai由 GitHub 账号 fourleafai 发布v1.1.0更新于 Oct 27, 2026

Job search and interview prep MCP. 15 tools, OAuth 2.1, cross-LLM. four-leaf.ai.

已验证Streamable HTTP可网页运行效率与工作流知识与记忆

概览

AI 生成的概览

托管的求职与面试准备 MCP,让助手获取真实职位、岗位情报、答案评分、简历匹配与薪资调研。

可以做什么
  • 用自然语言检索 14 万条以上在招职位,并展开完整职位描述
  • 生成贴合岗位的练习题,并按五维评分标准为输入的答案打分
  • 将简历与职位描述比对打分并指出差距
  • 调研薪酬,包括带引用的薪资区间与 offer 分析
  • 读取和写入求职申请追踪表
  • 获取特定岗位的面试情报与面试策略建议
适用场景
适合正在找工作或准备某场具体面试的人,希望助手基于真实职位、按评分标准给出的练习反馈和实时薪资数据来工作,而不是泛泛建议。
运行要求
远程 HTTP 端点,使用 OAuth 2.1 认证,首次调用工具时会打开浏览器登录。数据类工具需要免费的 Four-Leaf 账号(含 3 天试用,无需信用卡)。可选的辅导 Skill 需另行通过 npx 安装,未接入 MCP 时以仅辅导的降级模式运行。
安装前请注意
OAuth 登录会授予服务器访问你账号的权限;申请追踪表会保存你添加的职位。免费账号有六项工具受每日次数限制,语音模拟面试与完整 AI 简历定制为付费功能。简历文本与职位描述会发送到该托管服务。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Clover Public,将其添加到工作区。
  2. 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
  3. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.fourleafai%2Fclover-public/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。

{
  "mcpServers": {
    "clover-public": {
      "type": "http",
      "url": "https://four-leaf.ai/api/mcp"
    }
  }
}

README

four-leaf-coach

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.

What it does

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:

  • Kickoff the coach reads your application tracker, figures out what you're prepping for, and routes you. Say "help me get ready for my job search" or "where am I with everything".
  • Find jobs natural-language search across 140,000+ active postings, then pull up a full posting and save it to your tracker. Say "find me remote senior data scientist roles".
  • Prep for a role interview pipeline, what to expect, how to win. Say "what's the interview like for a PM at Stripe".
  • Practice calibrated questions, then type your answer and get it scored 1-10 against the same five-dimension rubric the Four-Leaf practice page uses. Say "give me a few hard system design questions".
  • Analyze a JD scores a resume against a posting and points out gaps. Say "how does my resume stack up against this JD".
  • Negotiate and comp research real numbers from the MCP. Have an offer? It runs a full analysis (total comp, market percentile, red flags, a counter strategy with exact talking points). Just asking what a role pays? It returns a cited salary band from a live web search. Say "they made an offer, help me negotiate", "is this offer any good", or "what's a good salary for a backend engineer in Austin".
  • Interview strategy formats, AI interviewers, work trials, signal vs noise. Say "what are AI interviews actually like".

Install

Two steps. The Skill tells your AI tool how to coach. The hosted MCP gives the Skill live data.

Step 1: install the Skill

bash
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 <name> pick the tool yourself: claude-code, cursor, codex, or github-copilot
  • --scope <project|global> Claude Code only; where to install
  • --dry-run show what it would do without writing anything
  • --yes skip confirmation prompts, --force overwrite an existing install
  • four-leaf-coach list show the supported tools and what's detected in the current directory

Cursor needs the Nightly channel with Settings, Rules, Agent Skills enabled. The other tools work out of the box.

Step 2: install the Four-Leaf MCP for live data

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:

bash
# Claude Code, Claude Desktop, and any tool that uses claude-mcp configclaude 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.

Step 3: use it

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.)

Manual install

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 <name> automates.

bash
git clone https://github.com/fourleafai/clover-public.gitcd clover-publicnpm run build

npm run build reads skills/four-leaf-coach/SKILL.md plus the adjacent references/ tree and writes a dist/<tool>/ directory for each supported tool. Then copy your tool's bundle into place:

ToolBuild outputCopy 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 CLIdist/codex/cp -r dist/codex/AGENTS.md dist/codex/references PROJECT/, then run Codex from PROJECT
GitHub Copilotdist/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.

What's free vs paid

  • Free: the Skill itself, and thirteen of the fifteen MCP tools. That's jobs and full postings, role intel, the question bank, answer scoring, match scoring, comp research, and reading and writing your application tracker. Six of them carry a daily cap on a free account (job search 30/day; question generation, answer scoring, match scoring, and the two comp tools 20/day each, on separate counters). The rest are unmetered.
  • Paid on four-leaf.ai: two tools. Voice mock interviews with spoken answers and adaptive AI follow-ups, and full AI resume tailoring against a specific JD. A paid plan also lifts the daily caps above. Three options at four-leaf.ai/pricing. 3-day free trial (no card), $5 5-Day Pass, $20/mo Pro. All three give you the same features.

The Skill surfaces these when they're the right next step. It doesn't push.

FAQ

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.

Repo layout

README.md                    you are hereLICENSE                      MITpackage.json                 CLI + build wiring, npm metadatabin/  four-leaf-coach.js         the `npx four-leaf-coach add` CLIscripts/  build.js                   generates dist/<tool>/ 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 installskills/  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.mddist/                        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.

Roadmap

  • Registry submissions to every Skill aggregator that ships a public registry.
  • Coverage for more tools as their Skill conventions stabilize: Pi, Gemini CLI, OpenCode, Trae, Rovo Dev, Qoder.

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.

Contributing

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.

License

MIT. See LICENSE.

来源:README.md,提交 af34293

工具

0
该服务器需要登录,因此 SourceWeft 无法在没有账号的情况下读取其工具,也未收录。已连接账号所能看到的内容可能因账号及其权限而异。

版本历史

2
  1. v1.1.0最新Sep 22, 2026
  2. v1.0.0Sep 16, 2026

评分

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