Resume Optimizer
The repository is cloned using git.
The server source is hosted on GitHub and cloned from there for installation.
Imports and exports resumes in Markdown, using Markdown as the unified intermediate format.
Dependencies are installed via npm.
Optionally uses an OpenAI-compatible API (via OPENAI_API_KEY) to let the Agent perform resume polishing independently without relying on the host model.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Resume OptimizerOptimize my resume /Users/me/resume.docx for this job description: backend engineer, Python, AWS"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Resume Optimizer Agent · 程序员简历优化 Agent
一个跨应用的简历优化 Agent: 以 MCP Server 为核心, 兼容 ZCode / Cursor / Claude Desktop 等所有支持 MCP 的应用, 同时以 DeepSeek / OpenAI 兼容 API 独立运行; 附带 ZCode 插件打包。
诚实声明(重要): 本 Agent 帮你把真实经历表达得最好(STAR 法则、量化成果、JD 关键词对齐、专业措辞), 但不虚构公司、职位、时间、学历或数据。伪造经历会在入职背调(前雇主核实、社保记录比对)中暴露, 导致 offer 作废甚至行业拉黑——这条路我们不帮用户走。
功能
功能 | 说明 |
多格式导入 |
|
完整度分析 | 分区识别(中英双语)、0-100 评分、缺失/偏弱项、真实信息补充问题清单 |
JD 关键词匹配 | 提取 JD 关键词(含中文), 报告简历中缺失的关键词 |
AI 润色 | 不编造事实的前提下: 强动词、STAR、量化表达、技能分层、关键词对齐 |
多格式导出 | Markdown / PDF(自动探测系统中文字体) / Word(.docx) |
Related MCP server: Resume Assistant MCP
四个 MCP 工具
工具 | 作用 |
| 导入简历文件 → Markdown |
| 结构/完整度分析 + 补充信息问题清单 + JD 关键词匹配 |
| 润色简历(有 API Key 时直接调用 LLM; 否则返回指令由宿主模型执行) |
| 导出 md / pdf / docx |
快速开始
1. 获取并安装依赖
git clone https://github.com/zhoubiao188/resume-optimizer-agent.git
cd resume-optimizer-agent
npm install --omit=dev2. 接入你的应用
ZCode(MCP 配置或插件方式, 见下) / Cursor ~/.cursor/mcp.json:
{
"mcpServers": {
"resume-optimizer": {
"command": "node",
"args": ["/绝对路径/resume-optimizer-agent/src/server.mjs"]
}
}
}Claude Desktop (claude_desktop_config.json)、WorkBuddy 等其他支持 MCP 的应用同理: command: node, args: [src/server.mjs 的绝对路径]。
3. (可选) 让 Agent 自带大脑
不配置时, 润色由宿主应用中的模型完成(工具会返回完整润色指令)。配置任一 API Key 后, Agent 独立完成润色:
export DEEPSEEK_API_KEY=sk-xxx # 或
export OPENAI_API_KEY=sk-xxx # 兼容任何 OpenAI 协议端点
export OPENAI_BASE_URL=https://xxx/v1 # 可选4. 作为 ZCode 插件安装
本仓库同时是一个标准 ZCode 插件(skill + MCP server 双组件):
# 克隆后在 ZCode 中: 插件市场 → 添加 → 添加插件市场 → 选择本仓库克隆目录
# 然后在市场中安装 "程序员简历优化 Agent"使用示例(在支持 MCP 的对话应用中)
帮我优化这份简历 /Users/me/resume.docx, 目标岗位 JD 如下: ……
Agent 会: 导入 → 分析(告知缺失项) → 向你提问补充真实信息 → 润色 → 按需导出 pdf/docx。
开发
npm install
npm test # 端到端: 导入→分析→导出(md/pdf/docx)→回读验证 + MCP 协议握手/工具调用目录结构
src/server.mjs MCP Server 入口(4 个工具)
src/importer.mjs md/txt/docx/pdf 导入
src/exporter.mjs md/pdf/docx 导出(PDF 内置中文字体探测)
src/analyzer.mjs 结构分析/评分/问题清单/JD 关键词
src/optimizer.mjs LLM 润色(DeepSeek/OpenAI 兼容) + 宿主指令生成
skills/ ZCode 插件技能定义(工作流程 + 诚信约束)
.zcode-plugin/ ZCode 插件清单
docs/publish-guide.md 各应用市场接入状态与步骤License
MIT
This server cannot be deployed
Maintenance
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