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URL: https://glama.ai/mcp/servers/jhgaylor/node-candidate-mcp-server

⇱ candidate-mcp-server by jhgaylor | Glama

Candidate MCP Server Library

A Model Context Protocol (MCP) server that gives LLMs access to information about a candidate.

Overview

Important: This server is intended to be used as a library to be integrated into other applications, not as a standalone service. The provided startup methods are for demonstration and testing purposes only.

Resources

This MCP server provides the following resources:

  • candidate-info://resume-text: Resume content as text

  • candidate-info://resume-url: URL to the resume

  • candidate-info://linkedin-url: LinkedIn profile URL

  • candidate-info://github-url: GitHub profile URL

  • candidate-info://website-url: Personal website URL

  • candidate-info://website-text: Content from the personal website

Tools

This MCP server also provides tools that return the same candidate information:

  • get_resume_text: Returns the candidate's resume content as text

  • get_resume_url: Returns the URL to the candidate's resume

  • get_linkedin_url: Returns the candidate's LinkedIn profile URL

  • get_github_url: Returns the candidate's GitHub profile URL

  • get_website_url: Returns the candidate's personal website URL

  • get_website_text: Returns the content from the candidate's personal website

  • contact_candidate: Sends an email to the candidate (requires Mailgun configuration)

Related MCP server: LinkedIn MCP Server

Usage

npm install @jhgaylor/candidate-mcp-server

Library Usage

This package is designed to be imported and used within your own applications.

Stdio

Starting the process is a breeze with stdio. The interesting part is providing the candidate configuration.

Where you source the candidate configuration is entirely up to you. Maybe you hard code it. Maybe you take a JSONResume url when you start the process. It's up to you!

import { createServer } from '@jhgaylor/candidate-mcp-server';
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";

// Configure your server
const serverConfig = { 
 name: "MyCandidateServer", 
 version: "1.0.0",
 mailgunApiKey: process.env.MAILGUN_API_KEY,
 mailgunDomain: process.env.MAILGUN_DOMAIN
};
const candidateConfig = { 
 name: "John Doe",
 email: "john.doe@example.com", // Required for the contact_candidate tool
 resumeUrl: "https://example.com/resume.pdf",
 // other candidate properties
};

// Create server instance
const server = createServer(serverConfig, candidateConfig);

// Connect with your preferred transport
await server.connect(new StdioServerTransport());
// or integrate with your existing HTTP server

StreamableHttp

Using the example code provided by the typescript sdk we can bind this mcp server to an express server.

import express from 'express';
import { Request, Response } from 'express';
import { createServer } from '@jhgaylor/candidate-mcp-server';
import { StreamableHTTPServerTransport } from "@modelcontextprotocol/sdk/server/streamablehttp.js";

// Configure your server
const serverConfig = { 
 name: "MyCandidateServer", 
 version: "1.0.0",
 mailgunApiKey: process.env.MAILGUN_API_KEY,
 mailgunDomain: process.env.MAILGUN_DOMAIN,
 contactEmail: "john.doe@example.com",
};
const candidateConfig = { 
 name: "John Doe",
 resumeUrl: "https://example.com/resume.pdf",
 // other candidate properties
};

// Factory function to create a new server instance for each request
const getServer = () => createServer(serverConfig, candidateConfig);

const app = express();
app.use(express.json());

app.post('/mcp', async (req: Request, res: Response) => {
 // In stateless mode, create a new instance of transport and server for each request
 // to ensure complete isolation. A single instance would cause request ID collisions
 // when multiple clients connect concurrently.
 
 try {
 const server = getServer(); 
 const transport = new StreamableHTTPServerTransport({
 sessionIdGenerator: undefined,
 });
 res.on('close', () => {
 console.log('Request closed');
 transport.close();
 server.close();
 });
 await server.connect(transport);
 await transport.handleRequest(req, res, req.body);
 } catch (error) {
 console.error('Error handling MCP request:', error);
 if (!res.headersSent) {
 res.status(500).json({
 jsonrpc: '2.0',
 error: {
 code: -32603,
 message: 'Internal server error',
 },
 id: null,
 });
 }
 }
});

app.get('/mcp', async (req: Request, res: Response) => {
 console.log('Received GET MCP request');
 res.writeHead(405).end(JSON.stringify({
 jsonrpc: "2.0",
 error: {
 code: -32000,
 message: "Method not allowed."
 },
 id: null
 }));
});

app.delete('/mcp', async (req: Request, res: Response) => {
 console.log('Received DELETE MCP request');
 res.writeHead(405).end(JSON.stringify({
 jsonrpc: "2.0",
 error: {
 code: -32000,
 message: "Method not allowed."
 },
 id: null
 }));
});

// Start the server
const PORT = process.env.PORT || 3000;
app.listen(PORT, () => {
 console.log(`MCP Stateless Streamable HTTP Server listening on port ${PORT}`);
});

Express

Instead of writing the binding between express and the mcp transport yourself, you can use express-mcp-handler to do it for you.

npm install express-mcp-handler

import express from 'express';
import { statelessHandler } from 'express-mcp-handler';
import { createServer } from './server';

// You can configure the server factory to include Mailgun settings
const createServerWithConfig = () => {
 const serverConfig = { 
 name: "MyCandidateServer", 
 version: "1.0.0",
 mailgunApiKey: process.env.MAILGUN_API_KEY,
 mailgunDomain: process.env.MAILGUN_DOMAIN,
 contactEmail: "john.doe@example.com",
 };
 const candidateConfig = { 
 name: "John Doe",
 resumeUrl: "https://example.com/resume.pdf",
 // other candidate properties
 };
 
 return createServer(serverConfig, candidateConfig);
};

// Configure the stateless handler
const handler = statelessHandler(createServerWithConfig);

// Create Express app
const app = express();
app.use(express.json());

// Mount the handler (stateless only needs POST)
app.post('/mcp', handler);

// Start the server
const PORT = process.env.PORT || 3002;
app.listen(PORT, () => {
 console.log(`Stateless MCP server running on port ${PORT}`);
});

Development

# Install dependencies
npm install

# Build the project
npm run build

# Run in development mode with auto-restart
npm run dev

Demo / Debug Startup via stdio

# Start with STDIO (demo only)
npm start

When running with STDIO, you can interact with the server by sending MCP messages as single-line JSON objects:

# Example of sending an initialize message via STDIO
echo '{"jsonrpc": "2.0","id": 1,"method": "initialize","params": {"protocolVersion": "2024-11-05","capabilities": {"roots": {"listChanged": true},"sampling": {}},"clientInfo": {"name": "ExampleClient","version": "1.0.0"}}}' | node dist/index.js --stdio

# List resources
echo '{"jsonrpc": "2.0","id": 2,"method": "resources/list","params": {}}' | node dist/index.js --stdio

# Access a resource
echo '{"jsonrpc": "2.0","id": 3,"method": "resources/read","params": {"uri": "candidate-info://resume-text"}}' | node dist/index.js --stdio

# List Tools
echo '{"jsonrpc": "2.0","id": 2,"method": "tools/list","params": {}}' | node dist/index.js --stdio

# Call a tool
echo '{"jsonrpc": "2.0","id": 4,"method": "tools/call","params": {"name": "get_resume_text", "args": {}}}' | node dist/index.js --stdio

# Send an email to the candidate
echo '{"jsonrpc": "2.0","id": 5,"method": "tools/call","params": {"name": "contact_candidate", "args": {"subject": "Hello from AI!", "message": "This is a test email sent via the MCP server.", "reply_address": "recruiter@company.com"}}}' | node dist/index.js --stdio

Each message must be on a single line with no line breaks within the JSON object.

Features

  • Library-first design for integration into other applications

  • Modular resource system for extending with custom candidate information

  • TypeScript for type safety and better developer experience

  • Implements the full Model Context Protocol specification

  • Supports multiple transport types (STDIO, HTTP, Streamable HTTP)

  • Minimal dependencies

Server Structure

src/
 ├── index.ts # Main package entry point
 ├── server.ts # MCP server factory with configuration
 ├── config.ts # Configuration type definitions
 └── resources/ # Modular resource definitions
 └── index.ts # Resource factory and implementation

MCP Protocol

This library implements the Model Context Protocol (MCP), a standardized way for LLMs to interact with external data and functionality. When integrated into your application, it exposes a stateless API that responds to JSON-RPC requests.

API Usage

Once integrated into your application, clients can interact with the MCP server by sending JSON-RPC requests. Here are examples of requests that your application would handle after integrating this library:

Initialize

curl -X POST http://your-application-url/mcp \
 -H "Content-Type: application/json" \
 -H "Accept: application/json" \
 -H "Accept: text/event-stream" \
 -d '{
 "jsonrpc": "2.0",
 "id": 1,
 "method": "initialize",
 "params": {
 "protocolVersion": "2024-11-05",
 "capabilities": {
 "roots": {
 "listChanged": true
 },
 "sampling": {}
 },
 "clientInfo": {
 "name": "ExampleClient",
 "version": "1.0.0"
 }
 }
 }'

Access Candidate Resources

curl -X POST http://your-application-url/mcp \
 -H "Content-Type: application/json" \
 -H "Accept: application/json" \
 -H "Accept: text/event-stream" \
 -d '{
 "jsonrpc": "2.0",
 "method": "resources/read",
 "params": {
 "uri": "candidate-info://resume-text"
 },
 "id": 2
 }'

Extending the Library

This library is designed to be extended with custom resources, tools, and prompts. Here's how to add your own resources:

import { McpServer, Resource } from '@jhgaylor/candidate-mcp-server';

// Create your custom resource class
class CustomCandidateResource extends Resource {
 constructor(candidateConfig) {
 super(
 `${candidateConfig.name} Custom Data`, 
 "candidate-info://custom-data", 
 async () => {
 return {
 contents: [
 { 
 uri: "candidate-info://custom-data", 
 mimeType: "text/plain", 
 text: "Your custom candidate data here"
 }
 ]
 };
 }
 );
 }
}

// Create server with standard configuration
const server = createServer(serverConfig, candidateConfig);

// Add your custom resource
const customResource = new CustomCandidateResource(candidateConfig);
customResource.bind(server);

// Connect with preferred transport
// ...

Adding Custom Tools

You can also extend the library with custom tools:

import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
import { z } from 'zod';
import { createServer } from '@jhgaylor/candidate-mcp-server';

// Create server with standard configuration
const server = createServer(serverConfig, candidateConfig);

// Add a custom tool
server.tool(
 'get_candidate_skills',
 'Returns a list of the candidate skills',
 {},
 async (_args, _extra) => {
 return {
 content: [
 { 
 type: "text", 
 text: "JavaScript, TypeScript, React, Node.js, MCP Protocol" 
 }
 ]
 };
 }
);

// Connect with preferred transport
// ...

Requirements

  • Node.js 20+

  • npm or yarn

License

MIT

Publishing to npm

Log in to npm if you haven't already:

npm login

Publish the package to npm (will run your prepublishOnly build):

npm publish

To bump, tag, and push a new version:

npm version patch # or minor, major
git push origin main --tags
A
license - permissive license
-
quality - not tested
C
maintenance

Maintenance

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