Resume MCP Server
Exposes a structured professional resume as a set of AI-queryable tools, enabling AI clients like Claude Desktop to query summary, experience, skills, projects, and tailor resumes to job descriptions.
README
Resume MCP Server
AI-powered Resume MCP Server built with the Model Context Protocol (MCP), TypeScript, Express, and the official MCP SDK.
Expose resume information as structured AI tools over both stdio and HTTP transports for seamless integration with MCP-compatible AI clients.
🌐 Live Deployment
| Endpoint | URL |
|---|---|
| MCP Endpoint | https://resume-mcp-server-z04b.onrender.com/mcp |
| Health Check | https://resume-mcp-server-z04b.onrender.com/health |
| Deployment Platform | Render (Free Tier) |
💡 Why This Project?
Although a resume can easily be uploaded as a PDF, this project demonstrates how structured information can be exposed to AI applications using the Model Context Protocol.
Instead of treating the resume as an unstructured document, AI clients can retrieve specific information through dedicated tools — skills, projects, education, experience, keyword search, and resume tailoring — with structured, predictable responses.
The same architecture can be extended to enterprise systems like HR platforms, CRMs, hospital databases, ERP systems, and internal business applications.
This is exactly why MCP exists — to give AI agents structured, programmatic access to data sources instead of relying on raw document parsing.
✅ Project Highlights
| ✔ | Built using the official MCP SDK |
| ✔ | Supports both stdio and HTTP/Streamable transports |
| ✔ | Deployed on Render with a live public endpoint |
| ✔ | Integrated with Claude Desktop (stdio) |
| ✔ | Integrated with Cursor AI (HTTP) |
| ✔ | 8 fully functional AI Tools |
| ✔ | Full TypeScript implementation with Zod validation |
| ✔ | Automated test suite — 16/16 stdio + 6/6 HTTP tests passing |
🏗️ Architecture
Local (stdio Transport)
Claude Desktop
│
│ stdin / stdout (stdio)
│
Resume MCP Server (node dist/stdioMain.js)
│
│ reads
│
resume.json
Remote (HTTP Transport)
Cursor AI / Claude Desktop / Any MCP Client
│
│ POST /mcp (HTTP + Streamable)
│
Render.com
│
Resume MCP Server (node dist/httpMain.js)
│
│ reads
│
resume.json
🧪 Tested AI Clients
| Client | Transport | Status |
|---|---|---|
| Claude Desktop | stdio | ✅ Tested & Working |
| Cursor AI | HTTP | ✅ Tested & Working |
| Render Deployment | HTTP/Streamable | ✅ Tested & Working |
| MCP Inspector | stdio | ✅ Tested & Working |
| Claude Web | — | ⚠️ Currently doesn't support arbitrary custom MCP servers |
| ChatGPT | — | ⚠️ Currently doesn't support connecting to custom MCP servers |
🌍 Possible Business Use Cases
This architecture can be adapted far beyond a personal resume:
| Use Case | Description |
|---|---|
| Employee Database MCP | HR teams query employee skills, roles, and history via AI |
| Hospital Records MCP | AI retrieves patient records, appointments, or prescriptions |
| CRM Assistant | AI queries customer data, leads, and deal history |
| HR Recruitment Assistant | AI screens candidates and matches JDs to profiles |
| ERP Systems | AI fetches inventory, orders, and financial records |
| Knowledge Base | AI searches internal company documentation |
| Company Documentation | AI answers policy and process questions |
| GitHub Repository Assistant | AI queries codebase structure, contributors, and issues |
The MCP architecture in this project is the same pattern used in all of these enterprise scenarios.
✨ Features
| Feature | Description |
|---|---|
| 8 MCP Tools | Query summary, experience, skills, projects, education, search, fetch by ID, and tailor resume to a JD |
| Two Transport Modes | stdio (local, zero-config) and HTTP/Streamable (remote, deployable) |
| Resume Tailoring | Rule-based keyword overlap analysis — matches your resume against any job description |
| Full-Text Search | Search across all resume sections with stable IDs for drill-down |
| Optional API Key Auth | Protect your HTTP endpoint with x-api-key header validation |
| Health Check Endpoint | GET /health for uptime monitoring and deployment health checks |
| Type-Safe | Written in strict TypeScript with Zod schema validation |
🛠️ Available Tools
getSummary
Returns the candidate's name, professional title, summary, and contact information.
- Parameters: None
- Example prompt: "What is this candidate's professional summary?"
getExperience
Returns work experience history. Optionally filter by company name (case-insensitive partial match).
- Parameters:
company(optional string) — e.g."RBrickks" - Example prompt: "What companies has this person worked at?"
getSkills
Returns skills organized by category. Optionally filter to a specific category.
- Parameters:
category(optional enum) —"languages"|"frameworks"|"tools"|"soft" - Example prompt: "What programming languages does this candidate know?"
getProjects
Returns projects built by the candidate. Optionally filter by technology stack tag.
- Parameters:
tag(optional string) — e.g."Angular","Spring Boot" - Example prompt: "Show me projects that use Angular"
getEducation
Returns the academic education history with degrees, institutions, and grades.
- Parameters: None
- Example prompt: "Where did this candidate study?"
search
Full-text search across all resume sections — summary, experience bullets, skills, project descriptions, and education. Returns stable IDs that can be passed to fetch for full details.
- Parameters:
query(required string) — e.g."Spring Boot","automation" - Example prompt: "Search the resume for anything related to security"
fetch
Fetches the complete details of a specific resume section by its stable ID (returned by search).
- Parameters:
id(required string) — e.g."summary","experience-0","projects-1","skills","education-2" - Example prompt: "Get the full details for experience-0"
tailorResume
Analyzes a job description and ranks the most relevant skills, experience bullets, and projects by keyword overlap. Purely rule-based — no external AI dependency.
- Parameters:
jobDescription(required string) — the full text of a job posting - Example prompt: "Here's a job description for a Java backend role at Google: [paste JD]. How well does this resume match?"
📦 Prerequisites
- Node.js v18 or higher
- npm (included with Node.js)
🚀 Installation
# Clone the repository
git clone https://github.com/Adarshcharjan/resume-mcp-server.git
cd resume-mcp-server
# Install dependencies
npm install
# Build TypeScript to JavaScript
npm run build
▶️ Running the Server
Option 1: stdio Transport (Local)
Designed for direct integration with AI clients running on the same machine (e.g., Claude Desktop). The client launches the server process and communicates via standard input/output.
npm run dev:stdio
Option 2: HTTP Transport (Local or Remote)
Runs as a standard web server. Use this for remote deployment or when the AI client connects over HTTP.
npm run dev:http
The server starts at http://localhost:3000 with:
- MCP endpoint:
POST http://localhost:3000/mcp - Health check:
GET http://localhost:3000/health
🔐 API Key Authentication
The HTTP server supports optional API-key authentication.
If RESUME_MCP_API_KEY is set in your environment variables, every request to /mcp must include the header:
x-api-key: your-secret-key
Otherwise the server runs in public mode (no authentication required).
Setting it up:
# Copy the example env file
cp .env.example .env
Edit .env:
PORT=3000
RESUME_MCP_API_KEY=your_custom_secret_key_here
When the API key is active, Claude Desktop config must include it:
{
"mcpServers": {
"resume": {
"type": "streamable-http",
"url": "https://your-server.onrender.com/mcp",
"headers": {
"x-api-key": "your_custom_secret_key_here"
}
}
}
}
🔌 Integrating with MCP-Compatible AI Clients
Claude Desktop
Claude Desktop supports MCP natively. You can connect using either transport mode.
stdio (Recommended for Local Use)
-
Open your Claude Desktop configuration file:
- Windows:
%APPDATA%\Claude\claude_desktop_config.json - macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
- Windows:
-
Add the
mcpServersentry (create the file if it doesn't exist):
{
"mcpServers": {
"resume": {
"command": "node",
"args": ["/absolute/path/to/resume-mcp-server/dist/stdioMain.js"]
}
}
}
⚠️ Windows users: Use double backslashes in the path:
"D:\\Study\\Resume _MCP_server\\dist\\stdioMain.js"
-
Restart Claude Desktop completely (quit from system tray, then reopen).
-
Start a new chat. The hammer 🔨 tools icon near the chat input will show all 8 resume tools.
HTTP / Streamable (Remote Server)
{
"mcpServers": {
"resume": {
"type": "streamable-http",
"url": "https://resume-mcp-server-z04b.onrender.com/mcp"
}
}
}
Cursor AI
-
Open Cursor Settings → MCP (or
Ctrl+Shift+P→ "MCP: Add Server"). -
Add a new server:
stdio:
{ "resume": { "command": "node", "args": ["/absolute/path/to/resume-mcp-server/dist/stdioMain.js"] } }HTTP (Recommended — uses the live Render deployment):
{ "resume": { "type": "streamable-http", "url": "https://resume-mcp-server-z04b.onrender.com/mcp" } } -
The resume tools will be available in Cursor's AI chat immediately.
VS Code + GitHub Copilot
- Create or edit
.vscode/mcp.jsonin your workspace:
{
"servers": {
"resume": {
"command": "node",
"args": ["/absolute/path/to/resume-mcp-server/dist/stdioMain.js"]
}
}
}
- Open GitHub Copilot Chat in Agent mode — the resume tools will be available.
Windsurf
-
Open Windsurf Settings → MCP.
-
Add a new server:
{
"resume": {
"type": "streamable-http",
"url": "https://resume-mcp-server-z04b.onrender.com/mcp"
}
}
MCP Inspector (Testing & Debugging)
The MCP Inspector is a visual tool for testing MCP servers without any AI client.
npx @modelcontextprotocol/inspector
When the Inspector UI opens in your browser:
- Set Transport Type →
STDIO - Set Command →
node - Set Arguments →
dist/stdioMain.js - Click Connect
All 8 tools will appear. Click any tool, fill in parameters, and hit Run to see live JSON responses.
☁️ Deployment on Render
This project is deployed on Render using the HTTP Streamable transport.
Configuration
| Setting | Value |
|---|---|
| Runtime | Node |
| Build Command | npm install && npm run build |
| Start Command | npm start |
| Plan | Free |
Environment Variables on Render
| Variable | Value |
|---|---|
PORT |
3000 |
RESUME_MCP_API_KEY |
(your secret key — optional) |
Note: Render's free tier spins down after 15 minutes of inactivity. The first request after a cold start may take ~30 seconds to respond.
🧪 Testing
Automated Test Suite — stdio (16 test cases)
npm run build
node test-all-tools.mjs
Expected output:
✓ PASS 1. getSummary — Name: Adarsh Charjan | Title: Junior Software Developer
✓ PASS 2. getExperience — Jobs returned: 3
✓ PASS 3. getExperience — filter "RBrickks" → 2 jobs
✓ PASS 4. getSkills — Languages: Java, SQL, HTML, CSS
✓ PASS 5. getSkills — filter "frameworks" → Spring Boot, Spring MVC, Hibernate, Angular, REST APIs
✓ PASS 6. getProjects — 2 projects returned
✓ PASS 7. getProjects — filter "Angular" → WELLCARE Hospital Management System
✓ PASS 8. getEducation — B.Tech, HSC, SSC
✓ PASS 9. search "Spring Boot" — 4 matches
✓ PASS 10. search "automation" — 2 matches
✓ PASS 11. fetch "summary" — Professional Summary
✓ PASS 12. fetch "experience-0" — Junior Software Developer at RBrickks Technology
✓ PASS 13. fetch "projects-1" — WELLCARE Hospital Management System
✓ PASS 14. fetch "skills" — Skills and Technologies
✓ PASS 15. tailorResume — Matched languages: [Java, SQL] | Top bullet score: 7
✓ PASS 16. fetch invalid id — Graceful error handling
Results: 16 passed 0 failed / 16 total 🎉
Automated Test Suite — HTTP (6 test cases)
# Terminal 1
npm run dev:http
# Terminal 2
node test-http.mjs
Expected output:
✓ PASS 1. initialize — Server: resume-mcp-server v1.0.0
✓ PASS 2. getSummary — Name: Adarsh Charjan
✓ PASS 3. getExperience — filter "AutomationEdge" → RPA Intern
✓ PASS 4. search "RBAC" — 3 matches
✓ PASS 5. tailorResume — Matched frameworks: [Spring Boot, Angular, REST APIs]
✓ PASS 6. GET /health — Status: ok
Results: 6 passed 0 failed / 6 total 🎉
📁 Project Structure
resume-mcp-server/
├── src/
│ ├── data/
│ │ ├── resume.json # Structured resume data
│ │ └── resumeLoader.ts # Type-safe JSON loader with interfaces
│ ├── tools/
│ │ ├── getSummary.ts # Returns name, title, summary, contact
│ │ ├── getExperience.ts # Work history with company filter
│ │ ├── getSkills.ts # Skills by category
│ │ ├── getProjects.ts # Projects with stack tag filter
│ │ ├── getEducation.ts # Education history
│ │ ├── search.ts # Full-text search across all sections
│ │ ├── fetch.ts # Fetch full record by stable ID
│ │ └── tailorResume.ts # JD keyword matching & ranking
│ ├── server.ts # McpServer factory — registers all 8 tools
│ ├── stdioMain.ts # Entry point: stdio transport (local)
│ └── httpMain.ts # Entry point: HTTP transport (remote)
├── dist/ # Compiled JavaScript (generated by npm run build)
├── test-all-tools.mjs # Automated stdio test suite (16 cases)
├── test-http.mjs # Automated HTTP test suite (6 cases)
├── package.json # Dependencies and npm scripts
├── tsconfig.json # TypeScript compiler configuration
├── .env.example # Environment variable template
├── .gitignore # Excludes node_modules, dist, .env
└── README.md # This file
📜 NPM Scripts
| Script | Command | Description |
|---|---|---|
npm run dev:stdio |
tsx src/stdioMain.ts |
Run locally with stdio transport (Claude Desktop) |
npm run dev:http |
tsx src/httpMain.ts |
Run locally with HTTP transport (development) |
npm run build |
tsc |
Compile TypeScript source to dist/ |
npm start |
node dist/httpMain.js |
Run compiled HTTP server (production/Render) |
🏗️ Tech Stack
| Technology | Purpose |
|---|---|
| TypeScript | Type-safe server implementation |
| @modelcontextprotocol/sdk | Official MCP SDK — tool registration and transport handling |
| Express | HTTP server framework for the remote transport |
| Zod | Runtime schema validation for tool parameters |
| tsx | TypeScript execution for development |
🛡️ Security
- API Key Authentication: When
RESUME_MCP_API_KEYis set, the HTTP server validates every/mcprequest. Requests with a missing or incorrect key receive401 Unauthorized. - CORS: The HTTP server includes full CORS headers to allow browser-based MCP clients to connect.
- No External AI Calls: The
tailorResumetool uses purely rule-based keyword matching. No resume data is sent to any external APIs or LLMs. .envexcluded from Git: Secrets never reach GitHub — only.env.example(with empty values) is committed.
📄 License
ISC
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。