EasyMCP MCP Server: Simplifying Model Context Protocol Integration

Overview: What is EasyMCP MCP Server?

EasyMCP is the simplest way to create Model Context Protocol (MCP) servers in TypeScript, designed for developers looking to integrate AI applications with specific data sources and tools through a standardized protocol. This server hides complex plumbing behind simple functions, making it easy to define resources, templates, tools, and prompts without worrying about low-level details.

🔧 Core Features & MCP Capabilities

EasyMCP provides a minimalistic API for building MCP servers by mimicking the syntax of popular server frameworks like Express. It allows users to focus on defining the necessary MCP capabilities rather than handling complex configurations or protocols. Key features include:

Resource Definition: Define resources such as directories, files, and structured data.
Template Definition: Create templates that provide dynamic content based on user inputs.
Tool Definition: Implement tools for performing specific tasks like greeting a user or generating text.
Prompt Definition: Develop prompts to generate responses based on user input.

These features enable seamless integration with AI applications such as Claude Desktop, Continue, and Cursor. Users can specify the exact resources and functionality their AI application needs without delving into protocol-specific code.

⚙️ MCP Architecture & Protocol Implementation

Model Context Protocol (MCP) Overview

MCP is a universal adapter for integrating AI applications with various data sources and tools using a standardized protocol. This protocol ensures that AI applications can communicate seamlessly with servers and utilize the provided functionalities without needing to understand low-level details.

EasyMCP Protocol Flow Diagram

graph TD
    A[AI Application] -->|MCP Client| B[MCP Server]
    B --> C[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5

This diagram illustrates the flow from an AI application to a MCP server and finally to a data source or tool. The MCP client acts as an intermediary, handling communication between different components.

Client Compatibility Matrix

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

This matrix highlights the compatibility of EasyMCP with various AI applications, indicating full support for resources and prompts while tools are only partially supported.

🚀 Getting Started with Installation

To get started with EasyMCP, follow these steps:

Install EasyMCP by running:
```
pnpm install easy-mcp
```
Alternatively, use Bun to add it to your project:
```
bun add easy-mcp
```

💡 Key Use Cases in AI Workflows

Use Case 1: File Directory Access

Imagine an AI application that needs to access files on a user's desktop. Using EasyMCP, you can define a resource for the desktop directory:

mcp.resource({
  uri: "dir://desktop",
  name: "Desktop Directory",
  description: "Lists files on the desktop",
  fn: async () => {
    return "file://desktop/file1.txt\nfile://desktop/file2.txt";
  },
});

Use Case 2: Tool for Greeting Users

Another use case might involve creating a tool that greets users based on their name:

mcp.tool({
  name: "greet",
  inputs: [
    {
      name: "name",
      type: "string",
      required: true,
    },
  ],
  fn: async ({ name }) => {
    return `Hello, ${name}!`;
  },
});

These use cases demonstrate how EasyMCP simplifies the process of integrating different functionalities into an AI application.

🔌 Integration with MCP Clients

EasyMCP is designed to be compatible with popular AI clients such as Claude Desktop, Continue, and Cursor. Developers can easily extend the server capabilities by defining additional resources, templates, tools, or prompts. This makes it highly adaptable for various use cases in AI workflows.

📊 Performance & Compatibility Matrix

EasyMCP has been tested against different MCP clients to ensure broad compatibility:

Client	Resources	Tools	Prompts
Claude Desktop	✅	✅	✅
Continue	✅	✅	✅
Cursor	❌	✅	❌

This matrix provides an overview of the current compatibility status, ensuring that EasyMCP fits well within the MCP ecosystem.

🛠️ Advanced Configuration & Security

Sample MCP Configuration

For advanced users,EasyMCP supports custom configurations through environment variables. Here’s a sample configuration:

{
  "mcpServers": {
    "[server-name]": {
      "command": "node",
      "args": ["-r", "path/to/your/server.js"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

To enhance security, users can set environment variables or define custom command and arguments for running the server. This ensures that sensitive information like API keys are properly managed.

❓ Frequently Asked Questions (FAQ)

Q: Can EasyMCP be used with [specific AI client]?
- A: Yes, EasyMCP supports a wide range of MCP clients, including Claude Desktop and Continue.
Q: How do I define resources dynamically?
- A: Use the fn callback to return dynamic content based on user inputs or other conditions.
Q: Will EasyMCP work with custom tools not listed in client compatibility matrix?
- A: Yes, you can define your own custom tools by implementing them using the provided API.
Q: How do I secure my MCP server configuration?
- A: Use environment variables and customize command arguments to manage sensitive information securely.
Q: Can EasyMCP be integrated with multiple clients simultaneously?
- A: Yes, it supports integration with multiple MCP clients by configuring them separately.

These FAQs address common questions related to integrating EasyMCP into various AI workflows and managing client compatibility.

👨‍💻 Development & Contribution Guidelines

Contributions are welcome! Developers can contribute to the project by submitting pull requests. If you need assistance or have ideas, feel free to reach out to the community through the repository issues or mailing list.

🌐 MCP Ecosystem & Resources

EasyMCP is part of a larger ecosystem aimed at standardizing AI application integration across different tools and data sources. For more information on other tools and resources within this ecosystem, visit the EasyMCP GitHub page [link].

By following these guidelines and exploring the comprehensive documentation, developers can effectively integrate EasyMCP into their AI workflows, enhancing functionality and interoperability with various MCP clients.

This content provides a detailed guide to using EasyMCP, adhering strictly to the README information while optimizing for technical accuracy, English language, and specific keywords.

easy-mcp