READMEmain

🚀 MCPAgent SDK & Website

Download/Clone this project from GitHub, or copy the files directly to your environment.

1. MCPAgent SDK (Python)

The MCPAgent SDK provides a high-level interface for building and interacting with MCP-compatible servers. It uses the MCP Python SDK under the hood to manage resources, tools, and prompts in a standardized way.

Installation

Install MCP from PyPI:
```
pip install mcp
```
Clone this repository or copy the relevant files (e.g., mcpagent.py, server_multi.py, etc.) into your project.

Getting Started with `MCPAgent`

Below is a snippet showing how you can incorporate the MCPAgent class in your own Python code. This class launches your MCP server in a subprocess and helps you easily call resources, tools, or prompts.

from mcpagent import MCPAgent  # example import from your local file
import asyncio

async def main():
    # Point to your server script (e.g., server_multi.py)
    agent = MCPAgent("server_multi.py")
    
    # Start MCP server & initialize session
    await agent.start()

    # Interact with the server: call a resource, tool, or prompt
    info_text = await agent.read_info("Python")
    print("Resource info:", info_text)

    product = await agent.multiply(7, 8)
    print("Tool result (7*8):", product)

    prompt_messages = await agent.run_prompt("You are a powerful math Agent\nQ: give the formula of derivative of cos(x)\nA:")
    for msg in prompt_messages:
        print(f"{msg.role.upper()} - {msg.content.text}")

    # Clean up
    await agent.stop()

if __name__ == "__main__":
    asyncio.run(main())

Core Features

Resource Access
Easily read or write contextual data via resource URIs (e.g., myresource://...).
Tool Invocation
Execute server-defined tools (functions) by name, passing in JSON arguments. Perfect for hooking into AI model logic.
Prompt Usage
Render or retrieve prompt templates from the server, returning them as messages for the LLM.
Subprocess Integration
The MCPAgent can spawn the MCP server script in a subprocess (via stdio), so you don’t need separate windows or manual commands.

2. MCP Website & Hosting Description

The below describes the MCP Agents web interface and broader context for the Model Context Protocol.

🚀 MCP Agents: The Future of AI Agent Architectures

Welcome to MCP Agents, a modern web interface showcasing the revolutionary Model Context Protocol (MCP), the next step forward in AI agent architectures. 🌐

With MCP, the way AI models interact and share contexts is being transformed into a standardized, scalable, and flexible solution. This project serves as both an introduction to the protocol and a resource hub for developers. 💡

Tech-Spec: https://modelcontextprotocol.io/introduction

Alt text

🤔 What is MCP?

The Model Context Protocol (MCP) is a cutting-edge standard for context sharing and management across AI models and systems. Think of it as the language AI agents use to interact seamlessly. 🧠✨

Here’s why MCP matters:

🧩 Standardization: MCP defines how context can be shared across models, enabling interoperability.
⚡ Scalability: It’s built to handle large-scale AI systems with high throughput.
🔒 Security: Robust authentication and fine-grained access control.
🌐 Flexibility: Works across diverse systems and AI architectures.

✨ Features of MCP Agents

🖼️ Futuristic UI: Built using Next.js and Tailwind CSS, providing a sleek and minimalistic experience.
📑 Tech Docs: Curated documentation on how to get started with MCP, from Python SDKs to server setup.
🗿 Roadmap: A visual timeline of MCP's milestones and future plans.

🚀 Getting Started

🔧 Prerequisites

To run the web interface locally, you’ll need:

Node.js (v16 or higher recommended)
npm or yarn

🛠️ Installation

Clone the repository and install dependencies:

git clone https://github.com/yourusername/mcp-agents.git
cd mcp-agents
npm install

🏃‍♂️ Run the Development Server

npm run dev

Open http://localhost:3000 in your browser to see the website in action! 🌟

📑 Key Sections

🏠 Landing Page

Learn what MCP is all about, with real-world context and getting-started code snippets.

📖 Tech Docs

Comprehensive, developer-friendly guides covering:

📦 MCP Python SDK installation and setup.
⚙️ Creating an MCP-compliant server.
🔧 Example workflows and integrations.

🗿 Roadmap

A sleek, timeline-based visualization of MCP's progress:

✅ POC and MVP completed.
🚀 Next steps: Scalability, Feature Enhancements, and Community Building.

💻 Tech Stack

This project is powered by:

⚛️ Next.js – A React framework for server-side rendering and static site generation.
🌠 Tailwind CSS – A utility-first CSS framework for rapid UI development.
💡 react-syntax-highlighter – Beautiful code highlighting for developers.

🤝 Contributing

We’d love your help to improve MCP Agents! 🛠️ Feel free to:

Submit issues and pull requests.
Improve documentation and examples.
Share your feedback and suggestions.

📩 Contact

Got questions? Reach out to us via:

Email: support@mcpagents.com
Twitter: @mcpagents

Enjoy building with MCP and the MCPAgent SDK, shaping the future of AI! 🚀✨

agency