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Volunteer Search Server

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Enables searching for volunteer opportunities via MCP protocol, REST API, and includes a custom Apex MCP client for Salesforce Agentforce integration, all power

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Enables searching for volunteer opportunities via MCP protocol, REST API, and includes a custom Apex MCP client for Salesforce Agentforce integration, all powered by the free VolunteerConnector API.

README

A Model Context Protocol (MCP) server, client demo, and REST API for searching volunteer opportunities from the free VolunteerConnector API.

License: MIT Node.js


🏆 What Makes This Special?

Most MCP implementations are either servers OR clients. This project has BOTH:

  1. MCP Server (Node.js) - Serves MCP protocol
  2. MCP Client (Apex) - Custom Salesforce MCP client
  3. MCP Client (JavaScript) - Browser-based demo
  4. REST API - Traditional HTTP endpoints
  5. Hybrid Architecture - All in one deployment

💡 Why the Apex MCP Client Matters:

Salesforce doesn't natively support MCP protocol. This project implements a full JSON-RPC 2.0 MCP client from scratch in Apex, making Salesforce Agentforce a first-class citizen in the MCP ecosystem.

This demonstrates:

  • Deep understanding of protocol specifications
  • Ability to implement AI protocols in enterprise platforms
  • Bridge between traditional enterprise (Salesforce) and cutting-edge AI (MCP)

🎯 Features

  • 🔌 MCP Server - True Model Context Protocol implementation (JSON-RPC 2.0)
  • 📱 Multiple MCP Clients - Apex (Salesforce), JavaScript (Browser), Claude Desktop
  • 💻 MCP Client Demo - Interactive web-based client for testing MCP over SSE
  • 🌐 REST API - HTTP endpoints for traditional integration
  • 🔄 Hybrid Mode - Single server supporting both REST and MCP protocols
  • ⚡ Salesforce Agentforce - Custom Apex MCP client for Agentforce integration
  • 💰 FREE - Uses VolunteerConnector API (no authentication required)
  • 🚀 Heroku Ready - Deploy to Heroku in 5 minutes
  • 🧪 Tested - Includes test scripts and live demos
  • 📚 Well Documented - Complete guides and examples

📦 What's Included

1. MCP Server (volunteer-search-server.js)

  • Implements Model Context Protocol (stdio)
  • Works with Claude Desktop and other MCP clients
  • Exposes 2 tools:
    • search_volunteer_opportunities - Search with filters
    • get_opportunity_details - Get full details by ID

2. MCP Client Demo (public/index.html)

  • Interactive web-based MCP client
  • Connects to MCP server via SSE (Server-Sent Events)
  • Real-time testing interface
  • Beautiful, modern UI
  • No backend required (pure frontend)

3. REST API (server.js)

  • Express.js REST API
  • Deployable to Heroku/Render/Railway
  • Endpoints:
    • GET / - API info
    • GET /health - Health check
    • POST /api/search - Search opportunities
    • GET /api/opportunity/:id - Get details

4. Hybrid Server (server-with-mcp-sse.js)

  • Supports BOTH REST API and MCP over SSE
  • Single deployment for multiple protocols
  • MCP endpoint: POST /mcp/message (JSON-RPC 2.0)
  • Serves MCP client demo at /
  • Perfect for production deployments

5. Salesforce Apex MCP Client (VTOApexMCPClient.cls)

  • Custom MCP client written in Apex
  • Implements JSON-RPC 2.0 protocol from scratch
  • Calls MCP server via HTTP POST
  • Usable in Salesforce Agentforce Agent Builder
  • Methods:
    • searchViaMCPProtocol - Search using MCP protocol
    • listMCPTools - Discover available MCP tools
  • Full protocol compliance - validates JSON-RPC responses
  • Production-ready enterprise MCP client

🚀 Quick Start

Option 1: MCP Client Demo (Interactive Web UI)

# Install dependencies
npm install

# Start the hybrid server (REST + MCP)
node server-with-mcp-sse.js

# Open in browser
open http://localhost:3000

What you get:

  • Interactive MCP client in your browser
  • Test volunteer searches in real-time
  • See MCP protocol messages
  • Beautiful UI for demos

Option 2: REST API (for Heroku/Salesforce)

# Install dependencies
npm install

# Start the REST API
npm start

# Test locally
curl http://localhost:3000/health

Option 3: MCP Server (for Claude Desktop)

# Install dependencies
npm install

# Start the MCP server
npm run start:mcp

Then add to Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "volunteer-search": {
      "command": "node",
      "args": ["/absolute/path/to/volunteer-search-mcp/volunteer-search-server.js"]
    }
  }
}

⚡ Salesforce Agentforce Integration

This project includes a custom Apex MCP client that allows Salesforce Agentforce to use the Model Context Protocol!

How It Works:

Salesforce Agentforce
    ↓
VTOApexMCPClient.cls (Apex MCP Client)
    ↓ JSON-RPC 2.0 Message
POST /mcp/message
    ↓
Hybrid Server (MCP Protocol Handler)
    ↓
VolunteerConnector API

MCP Message Example:

Request (from Apex):

{
  "jsonrpc": "2.0",
  "id": 42345,
  "method": "tools/call",
  "params": {
    "name": "search_volunteer_opportunities",
    "arguments": {
      "keywords": "tutoring",
      "location": "Toronto",
      "max_results": 5
    }
  }
}

Response (from server):

{
  "jsonrpc": "2.0",
  "id": 42345,
  "result": {
    "content": [
      {
        "type": "text",
        "text": "🌐 Found 5 volunteer opportunities...\n\n1. ..."
      }
    ]
  }
}

Key Features:

  • Full JSON-RPC 2.0 compliance
  • Protocol validation (checks jsonrpc version, message IDs)
  • Tool discovery (tools/list method)
  • Tool execution (tools/call method)
  • Enterprise logging (debug logs for troubleshooting)
  • Error handling (proper JSON-RPC error responses)

Why This Matters:

Most Salesforce integrations use REST. This project demonstrates that Salesforce can implement cutting-edge AI protocols like MCP through custom Apex clients.

This makes Salesforce a first-class citizen in the MCP ecosystem! 🚀


🌐 REST API Endpoints

GET /

Returns API information and available endpoints.

GET /health

Health check endpoint.

Response:

{
  "status": "ok",
  "timestamp": "2025-10-05T..."
}

POST /api/search

Search for volunteer opportunities.

Request Body:

{
  "keywords": "tutoring",
  "location": "Toronto",
  "remote_only": false,
  "max_results": 10
}

Response:

{
  "success": true,
  "total_count": 969,
  "returned_count": 10,
  "opportunities": [
    {
      "id": 43243,
      "title": "Event Planner",
      "organization": "Canadian Network for International Surgery",
      "description": "...",
      "url": "https://...",
      "dates": "September 8, 2025 - November 9, 2025",
      "duration": null,
      "remote": false,
      "location": "British Columbia",
      "activities": "Event Planning, Marketing, Social Media"
    }
  ],
  "formatted_text": "🌐 Found 10 volunteer opportunities..."
}

GET /api/opportunity/:id

Get detailed information about a specific opportunity.

Response:

{
  "success": true,
  "opportunity": {
    "id": 43243,
    "title": "Event Planner",
    "organization": "Canadian Network for International Surgery",
    "description": "...",
    "url": "https://...",
    "dates": "September 8, 2025 - November 9, 2025",
    "activities": [
      {"name": "Event Planning", "category": "PR, Fundraising, Events"}
    ]
  },
  "formatted_text": "📋 Volunteer Opportunity Details..."
}

🔧 MCP Tools

search_volunteer_opportunities

Search for volunteer opportunities with optional filters.

Parameters:

  • keywords (string, optional) - Search terms
  • location (string, optional) - City or region
  • remote_only (boolean, optional) - Filter for remote opportunities
  • max_results (number, optional) - Max results (1-50, default: 10)

Example:

{
  "keywords": "tutoring",
  "location": "Toronto",
  "max_results": 5
}

get_opportunity_details

Get detailed information about a specific opportunity.

Parameters:

  • opportunity_id (number, required) - The opportunity ID

Example:

{
  "opportunity_id": 43243
}

🚀 Deploy to Heroku

Quick Deploy:

# Login to Heroku
heroku login

# Create app
heroku create your-app-name

# Deploy
git init
git add .
git commit -m "Initial commit"
git push heroku main

# Open app
heroku open

Detailed Guide:

See HEROKU_DEPLOYMENT.md for complete deployment instructions.


🧪 Testing

Test REST API:

# Test locally
./test-api.sh http://localhost:3000

# Test on Heroku
./test-api.sh https://your-app.herokuapp.com

Test MCP Server:

# Use MCP Inspector
npx @modelcontextprotocol/inspector node volunteer-search-server.js

🔗 Integration Examples

Salesforce Apex

HttpRequest req = new HttpRequest();
req.setEndpoint('callout:Volunteer_Search_API/api/search');
req.setMethod('POST');
req.setHeader('Content-Type', 'application/json');

Map<String, Object> body = new Map<String, Object>{
    'keywords' => 'tutoring',
    'max_results' => 10
};
req.setBody(JSON.serialize(body));

Http http = new Http();
HttpResponse res = http.send(req);

JavaScript/Node.js

const response = await fetch('https://your-app.herokuapp.com/api/search', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    keywords: 'tutoring',
    max_results: 10
  })
});

const data = await response.json();
console.log(data.opportunities);

Python

import requests

response = requests.post(
    'https://your-app.herokuapp.com/api/search',
    json={
        'keywords': 'tutoring',
        'max_results': 10
    }
)

data = response.json()
print(data['opportunities'])

curl

curl -X POST https://your-app.herokuapp.com/api/search \
  -H "Content-Type: application/json" \
  -d '{"keywords":"tutoring","max_results":10}'

📊 Data Source

This project uses the VolunteerConnector API:


🏗️ Architecture

REST API Flow:

Client (Salesforce/Web/Mobile)
    ↓ HTTP REST
Express.js Server (server.js)
    ↓ HTTP GET
VolunteerConnector API
    ↓
Return formatted results

MCP Server Flow (stdio):

AI Assistant (Claude Desktop)
    ↓ MCP Protocol (stdio)
MCP Server (volunteer-search-server.js)
    ↓ HTTP GET
VolunteerConnector API
    ↓
Return formatted results

MCP Client Flow (SSE):

Web Browser (MCP Client Demo)
    ↓ MCP over SSE
Hybrid Server (server-with-mcp-sse.js)
    ↓ HTTP GET
VolunteerConnector API
    ↓
Return formatted results
    ↓ SSE Stream
Display in web UI

Hybrid Architecture:

┌───────────────────────────────────────────────────┐
│     Hybrid Server (server-with-mcp-sse.js)        │
├───────────────────────────────────────────────────┤
│                                                   │
│  ┌────────────────┐       ┌──────────────────┐   │
│  │   REST API     │       │   MCP Protocol   │   │
│  │   Endpoints    │       │   (JSON-RPC 2.0) │   │
│  │                │       │                  │   │
│  │ /api/search    │       │ /mcp/message     │   │
│  │ /api/opp/:id   │       │                  │   │
│  └────────┬───────┘       └─────────┬────────┘   │
│           │                         │            │
│           └──────────┬──────────────┘            │
│                      │                           │
│            ┌─────────▼──────────┐                │
│            │ VolunteerConnector │                │
│            │        API         │                │
│            └────────────────────┘                │
└───────────────────────────────────────────────────┘
            │                    │
            ▼                    ▼
    ┌──────────────┐     ┌─────────────────────┐
    │  Salesforce  │     │    MCP Clients:     │
    │  (REST API)  │     │  • Apex Client      │
    └──────────────┘     │  • Browser Client   │
                         │  • Claude Desktop   │
                         └─────────────────────┘

🔑 Key Difference:
   REST: Traditional HTTP API calls
   MCP:  JSON-RPC 2.0 protocol messages

Multiple Integration Patterns:

Client Type Protocol Endpoint Use Case
Salesforce (REST) HTTP REST /api/search Standard integration
Salesforce (MCP) JSON-RPC 2.0 /mcp/message Protocol-compliant AI
Web Browser JSON-RPC 2.0 /mcp/message Interactive demo
Claude Desktop MCP (stdio) N/A (stdio) Native AI assistant

📁 Project Structure

volunteer-search-mcp/
├── server.js                      # REST API server (Express.js)
├── server-with-mcp-sse.js         # Hybrid server (REST + MCP over SSE)
├── volunteer-search-server.js     # MCP server (stdio for Claude Desktop)
├── public/
│   └── index.html                 # MCP Client Demo (interactive web UI)
├── package.json                   # Dependencies
├── Procfile                       # Heroku configuration
├── test-api.sh                    # Test script
├── GETTING_STARTED.md             # Quick start guide
├── CLAUDE_DESKTOP_DEMO.md         # Claude Desktop setup guide
├── HEROKU_DEPLOYMENT.md           # Deployment guide
├── README.md                      # This file
├── LICENSE                        # MIT License
└── .gitignore                     # Git ignore rules

Salesforce Apex MCP Client (separate repo):
└── VTOApexMCPClient.cls           # Apex MCP client (JSON-RPC 2.0)
    └── VTOApexMCPClient.cls-meta.xml

🛠️ Development

Install Dependencies:

npm install

Run REST API (Development):

npm run dev

Run MCP Server (Development):

npm run dev:mcp

Test:

# Test REST API
./test-api.sh http://localhost:3000

# Test MCP Server
npx @modelcontextprotocol/inspector node volunteer-search-server.js

🌟 Use Cases

For Enterprises:

  • Salesforce Agentforce - Add volunteer search to AI agents (REST or MCP)
  • Corporate VTO Programs - Help employees find volunteer work
  • Volunteer Management Platforms - Integrate external volunteer opportunities
  • Mobile Apps - Find local volunteer opportunities
  • Nonprofit Websites - Display volunteer opportunities

For AI/ML Developers:

  • Claude Desktop - Native MCP integration via stdio
  • Custom AI Assistants - Add volunteer search to any MCP-compatible AI
  • Protocol Research - Study MCP client/server implementation
  • Multi-protocol Architecture - Learn REST + MCP hybrid patterns

For Learning & Demos:

  • Interactive Demos - Use web client for presentations and testing
  • Hackathons - Showcase MCP integration with live demo
  • Protocol Education - Learn JSON-RPC 2.0 and MCP specification
  • Salesforce Extensions - Example of custom Apex MCP client

📚 Resources


🤝 Contributing

Contributions are welcome! Feel free to:

  • Report bugs
  • Suggest features
  • Submit pull requests
  • Improve documentation

📄 License

MIT License - see LICENSE file for details.


🙏 Acknowledgments

  • VolunteerConnector for providing the free volunteer opportunities API
  • Anthropic for creating the Model Context Protocol
  • Heroku for easy deployment platform

📞 Support


🎉 Quick Links


Built with ❤️ for the volunteer community

Star ⭐ this repo if you find it useful!

from github.com/satishtamilan/volunteermcp

Installing Volunteer Search Server

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/satishtamilan/volunteermcp

FAQ

Is Volunteer Search Server MCP free?

Yes, Volunteer Search Server MCP is free — one-click install via Unyly at no cost.

Does Volunteer Search Server need an API key?

No, Volunteer Search Server runs without API keys or environment variables.

Is Volunteer Search Server hosted or self-hosted?

A hosted option is available: Unyly runs the server in the cloud, no local setup required.

How do I install Volunteer Search Server in Claude Desktop, Claude Code or Cursor?

Open Volunteer Search Server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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