
MCP Server on Cloudflare Workers & Azure Functions
A deployable MCP server for Cloudflare Workers or Azure Functions that provides example tools (time, echo, math), prompt templates for code assistance, and configuration resources. Enables AI assistants to interact with edge-deployed services through the Model Context Protocol.
README
MCP Server on Cloudflare Workers & Azure Functions
A Model Context Protocol (MCP) server that can be deployed to Cloudflare Workers or Azure Functions. This server provides tools, prompts, and resources that can be accessed via the MCP protocol, enabling AI assistants to interact with your deployed services.
Features
- 🚀 Deployed on Cloudflare Workers (edge computing)
- 🔧 Example tools:
get_time
,echo
,add
- 🌐 HTTP endpoints for health checks and MCP requests
- 📦 TypeScript with full type safety
- 🔄 Local development with Wrangler
Prerequisites
- Node.js 18+ installed
- A Cloudflare account (free tier works)
- npm or yarn package manager
Installation
Install dependencies:
npm install
Development
Run the development server locally:
npm run dev
This will start a local Cloudflare Workers environment at http://localhost:8787
Available Endpoints
Health Check
GET http://localhost:8787/health
Returns server status and version information.
MCP Protocol Endpoint
POST http://localhost:8787/mcp
Content-Type: application/json
{
"method": "tools/list"
}
Available Capabilities
Tools
The server includes three example tools with change notifications:
- get_time: Returns the current server time
- echo: Echoes back your message
- add: Adds two numbers together
Prompts
The server includes five prompt templates with change notifications:
- code_review: Get assistance reviewing code
- explain_concept: Get explanations of technical concepts
- debug_helper: Get help debugging issues
- api_design: Get guidance on API design
- refactor_suggestion: Get suggestions for refactoring code
Resource Access
The server provides contextual information through resources:
- config://server/info: Server metadata and configuration
- config://server/status: Current server status and metrics
- docs://mcp/getting-started: Getting started guide
Resources support:
- Subscriptions: Clients can subscribe to resource changes
- Templates: Parameterized resources (e.g.,
log://{level}/{message}
) - Multiple MIME types: JSON and Markdown content
Logging
Configurable logging with support for standard log levels:
- debug, info, notice, warning, error, critical, alert, emergency
Deployment
Option 1: Cloudflare Workers (Recommended for Edge)
1. Login to Cloudflare
npx wrangler login
2. Deploy to Cloudflare Workers
npm run deploy
Your MCP server will be deployed and you'll receive a URL like:
https://mcp-server.<your-subdomain>.workers.dev
Option 2: Azure Functions (Recommended for Azure Ecosystem)
For detailed Azure deployment instructions, see AZURE_DEPLOYMENT.md.
Quick Start
# Install dependencies
npm install
# Login to Azure
az login
# Deploy to Azure Functions
npm run deploy:azure
Your MCP server will be available at:
https://<your-function-app>.azurewebsites.net
Testing Deployed Server
# Health check
curl https://mcp-server.<your-subdomain>.workers.dev/health
# Test MCP endpoint
curl -X POST https://mcp-server.<your-subdomain>.workers.dev/mcp \
-H "Content-Type: application/json" \
-d '{"method": "tools/list"}'
Project Structure
.
├── src/
│ └── index.ts # Main server implementation
├── .github/
│ └── copilot-instructions.md
├── package.json # Dependencies and scripts
├── tsconfig.json # TypeScript configuration
├── wrangler.toml # Cloudflare Workers config
└── README.md # This file
Adding New Tools
To add a new tool, edit src/index.ts
:
- Add tool definition in
ListToolsRequestSchema
handler - Add tool implementation in
CallToolRequestSchema
handler
Example:
// In ListToolsRequestSchema handler
{
name: 'my_tool',
description: 'Description of what it does',
inputSchema: {
type: 'object',
properties: {
param1: {
type: 'string',
description: 'Parameter description',
},
},
required: ['param1'],
},
}
// In CallToolRequestSchema handler
case 'my_tool':
return {
content: [
{
type: 'text',
text: `Result: ${args.param1}`,
},
],
};
Configuration
Cloudflare Workers Settings
Edit wrangler.toml
to configure:
- Worker name
- Compatibility date
- KV namespaces (for storage)
- D1 databases (for SQL)
- Environment variables
Troubleshooting
Build Errors
Check TypeScript types:
npm run types
Deployment Issues
View deployment logs:
npx wrangler tail
Resources
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.