MCP Time Server - Streamable HTTP

⚠️ This Server is for Demo and Testing Purposes ⚠️

This is a bare bones example server designed for testing MCP Streamable HTTP protocol functionality. It is NOT intended for production use and lacks proper authentication and security measures.

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A Model Context Protocol (MCP) server providing time-related tools, implemented as a Cloudflare Worker.

This server allows LLMs to access various date/time functions.

Features

Provides the following MCP tools:

• current_time: Get the current date and time in specified formats and timezones.
• relative_time: Get a human-readable relative time string (e.g., "in 5 minutes", "2 hours ago").
• days_in_month: Get the number of days in a specific month.
• get_timestamp: Get the Unix timestamp (milliseconds) for a given time.
• convert_time: Convert a time between different IANA timezones.
• get_week_year: Get the week number and ISO week number for a given date.

Project Structure

mcp-server-http-time/
├── src/
│   └── index.ts      # Cloudflare Worker entry point & MCP logic
├── package.json      # Project dependencies and scripts
├── tsconfig.json     # TypeScript configuration
└── wrangler.toml     # Cloudflare Worker configuration

Getting Started

1. Clone the Repository:

   git clone https://github.com/Cam10001110101/mcp-server-http-time.git
   cd mcp-server-http-time
   

Development

1. Install Dependencies:

   npm install
   

2. Build: Compile the TypeScript code:

   npm run build
   

   (This compiles src/index.ts to dist/index.js)

3. Local Development (using Wrangler): Run the worker locally for testing:

   npx wrangler dev
   

   This will typically start the server on http://localhost:8787. You can then point your MCP client configuration to this local endpoint.

Deployment

Deploy the worker to Cloudflare:

npx wrangler deploy

(Ensure you are logged into Cloudflare via wrangler login first and have configured your wrangler.toml appropriately).

Connectors for Streamable HTTP Servers

NEW: Major providers have adopted the Model Context Protocol and now support Streamable HTTP servers directly. Anthropic, OpenAI, and Microsoft have all adopted this modern transport protocol.

📋 Protocol Note: Streamable HTTP is the modern replacement for the deprecated HTTP+SSE transport.

Anthropic MCP Connector

Anthropic's MCP Connector allows you to use Streamable HTTP servers directly through the Messages API without needing a separate MCP client.

The MCP Connector is perfect for this server since it uses the Streamable HTTP architecture. Simply include the server in your API requests:

curl https://api.anthropic.com/v1/messages \
  -H "Content-Type: application/json" \
  -H "X-API-Key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "anthropic-beta: mcp-client-2025-04-04" \
  -d '{
    "model": "claude-sonnet-4-20250514",
    "max_tokens": 1000,
    "messages": [{
      "role": "user", 
      "content": "What time is it in Tokyo?"
    }],
    "mcp_servers": [{
      "type": "url",
      "url": "https://your.worker.url.workers.dev",
      "name": "http-time-server"
    }]
  }'

Anthropic MCP Connector Benefits:

• No client setup required - Connect directly through the API
• Native Streamable HTTP support - Designed for servers like this one

OpenAI Agents SDK

OpenAI also supports Streamable HTTP servers through their Agents SDK using the MCPServerStreamableHttp class:

from agents.mcp.server import MCPServerStreamableHttp

# Connect to this Streamable HTTP server
server = MCPServerStreamableHttp({
    "url": "https://your.worker.url.workers.dev",
    "headers": {"Authorization": "Bearer your-token"},  # if needed
})

# Use the server in your OpenAI agent
await server.connect()
tools = await server.list_tools()
result = await server.call_tool("current_time", {"timezone": "Asia/Tokyo"})

Microsoft Copilot Studio

Microsoft Copilot Studio now supports Streamable HTTP servers with MCP integration generally available. You can connect this server to Copilot Studio by:

1. Building a custom connector that links your MCP server to Copilot Studio
2. Adding the tool in Copilot Studio by selecting 'Add a Tool' and searching for your MCP server
3. Using the server directly in your agents with generative orchestration enabled

More MCP Clients Coming Soon

Keep an eye out as more MCP clients adopt support for Streamable HTTP. Here are a few resources that maintain lists of MCP clients and their capabilities:

• PulseMCP Client Directory - Comprehensive list of MCP clients
• Official MCP Servers Repository - Official collection including client information
• MCP.so Client Listings - Community-maintained client directory

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Authentication & Security Considerations

⚠️ IMPORTANT: This example server has NO authentication or security measures implemented.

For production MCP servers, you should implement proper authentication as outlined in the official MCP documentation