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

Related MCP server: mundigital

💡 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

🏗️ 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

🌍 Possible Business Use Cases

This architecture can be adapted far beyond a personal resume:

🚀 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)

1. 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

2. Add the mcpServers entry (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"

3. Restart Claude Desktop completely (quit from system tray, then reopen).

4. 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

1. Open Cursor Settings → MCP (or Ctrl+Shift+P → "MCP: Add Server").

2. 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"
     }
   }

3. The resume tools will be available in Cursor's AI chat immediately.

📜 NPM Scripts

🛡️ Security

• API Key Authentication: When RESUME_MCP_API_KEY is set, the HTTP server validates every /mcp request. Requests with a missing or incorrect key receive 401 Unauthorized.

• CORS: The HTTP server includes full CORS headers to allow browser-based MCP clients to connect.

• No External AI Calls: The tailorResume tool uses purely rule-based keyword matching. No resume data is sent to any external APIs or LLMs.

• .env excluded from Git: Secrets never reach GitHub — only .env.example (with empty values) is committed.

📄 License

MIT © Adarsh Ravindra Charjan