- 🤖 AI Agents with MCP Server
🤖 AI Agents with MCP Server
Content
🤖 AI Agents with MCP Server
🚀 Overview
🧠 What Is This Project?
This project is a production-grade, modular framework for deploying AI agents via a Multi-Channel Processing (MCP) server. It enables real-time inference, multi-source data ingestion, and automated workflows using a plugin-based architecture.
It supports:
- Chat interaction using AI models like Google Gemini and OpenAI.
- Task execution such as arithmetic operations or social media posting.
- Integration of external tools through the Model Context Protocol (MCP).
🛠️ How Does It Work?
- Start the Server: Initializes and runs available tools/plugins.
- Interact via Client: Use a chat interface to send commands.
- AI Processes Input: Leverages AI models to generate responses and trigger plugins when needed.
🧩 Key Features
- 🧱 Modular Agent System — Plug-and-play agents using MCP SDK & Zod for schema validation
- ⚡ Real-Time Data Flow — Multi-channel input → AI inference → output pipeline
- 🔌 Extensible Architecture — Agent plugins, channel connectors, and utility modules
⚙️ Tech Stack
| Layer | Technology |
|---|---|
| Runtime | Node.js v16+ |
| Server | Express v5 + WebSocket |
| AI/ML | OpenAI API, Google GenAI |
| Validation | Zod |
| Messaging | MCP SDK v1.8.0 |
| Env | dotenv |
📦 Installation
Clone the repository:
git clone https://github.com/MuhammadTanveerAbbas/MCP-Server.git
cd ai-agents-mcp-server
Install dependencies:
npm install
Run the server:
npm start
📄 License
This project is licensed under the MIT License.
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