DIY MCP
A from-scratch implementation of the Model Context Protocol (MCP) for building servers and clients, using a Chinese tea collection as an example.
DIY MCP
A simple from-scratch implementation of the Model Context Protocol (MCP) for building MCP servers and clients using stdio. This example uses a simple Chinese tea collection with descriptions, origins, etc.
For production applications, check out the official MCP SDKs.
Project Structure
mcp/
├── server/ # MCP server for Chinese tea information
│ └── src/
│ ├── index.ts
│ ├── stdio.ts
│ └── teas.json
└── client/ # MCP client CLI with Claude as LLM
└── src/
├── index.ts
└── llm.ts
MCP Server
The core of this implementation is a lightweight MCP server. It offers the following resources and tools:
- Resources:
tea://teas: List of all available teastea://teas/{slug}: Details of a specific tea
- Tools:
getTeasByType: Get all teas of a specific typegetTeasByRegion: Get all teas from a specific province or region
Setup
cd server
npm install
npm run build
Running
You can test the MCP server with MCP Inspector, an interactive tool for testing and debugging MCP servers.
cd server
npm run inspector
MCP Client
You can interact with the MCP server through an MCP client like Claude Desktop, alternatively, you can use the included DIY MCP client. By adding your Anthropic API key, you can have Claude intelligently determine which tools to use based on your prompt.
The client provides three interaction modes:
- Ask LLM: Let Claude interact with the MCP server
- Get a resource: Directly access MCP server resources
- Use a tool: Directly call MCP server tools
Setup
cd client
npm install
To use Claude, first copy the example environment file and add your Anthropic API key with available credits to the ANTHROPIC_API_KEY variable:
cp .env.example .env
Running
The client will automatically start the MCP server, so ensure you've built it first.
cd server
npm run build
cd client
npm start
Usage
Once running, you can interact with the MCP server through the MCP client CLI. Try asking the LLM some questions about Chinese tea:
- "What teas do you know about?"
- "Which teas come from Fujian?"
- "What is your favorite green tea?"
Resources
İlgili Sunucular
Scout Monitoring MCP
sponsorPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
sponsorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
JSONPlaceholder
A free public REST API for testing and prototyping, powered by JSONPlaceholder.
Cargo MCP Server
Tools for managing Rust projects using the cargo command-line tool.
BlueMouse
The "Prefrontal Cortex" for LLMs. A local, data-driven logic gate that interviews AI to prevent hallucinations.
openapi-to-mcp
Expose API endpoints as strongly typed tools from an OpenAPI specification. Supports OpenAPI 2.0/3.0 in JSON or YAML format, from local or remote files.
Synth MCP
Access financial data like stock prices, currency info, and insider trading data using the Synth Finance API.
Svelte Documentation
Remote server (SSE/Streamable) for the latest Svelte and SvelteKit documentation
Remote MCP Server Authless
An example of a remote MCP server deployed on Cloudflare Workers without authentication.
MCP Context Server
Server providing persistent multimodal context storage for LLM agents.
MCP Server Creator
A meta-server for dynamically generating MCP server configurations and Python code.
Rails MCP Server
An MCP server for Rails projects, allowing LLMs to interact with your application.