Multi-MCP AI Agent
About
An AI agent which utilizes multiple MCP servers, including internal tools like math tools, and external tools like Google services and web scraping.
Details
- License
- MIT license
Explore
- Multi-MCP Architecture: Utilizes multiple MCP servers for distributed processing and diverse capabilities
- Cognitive Modules: Implements perception, decision-making, memory, and action modules
- External Service Integration:
- Google Workspace (Gmail, Google Drive, Google Sheets)
- Web scraping and content extraction
- DuckDuckGo search integration
- Real-time Communication:
- Telegram Bot interface
- Server-Sent Events (SSE) for live updates
- Core Components:
- Agent loop management
- Session handling
- Context management
- Strategic decision making
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Multi-MCP AI AgentCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
- Python 3.11+
- UV package manager
- Telegram Bot Token (for bot functionality)
- Google Cloud credentials (for Google Workspace integration)
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"multi-mcp ai agent": {
"multi-mcp-agent": {
"command": "uv",
"args": [
"venv"
]
}
}
}
}McpServers
{
"multi-mcp-agent": {
"command": "uv",
"args": [
"venv"
]
}
}An Agentic AI agent system that leverages multiple MCP (Model Control Protocol) servers to provide a wide range of capabilities, from basic mathematical operations to advanced external service integrations like Google Workspace and web scraping. The agent includes a Telegram bot interface and Server-Sent Events (SSE) for real-time communication.
🌟 Features
- Multi-MCP Architecture: Utilizes multiple MCP servers for distributed processing and diverse capabilities
- Cognitive Modules: Implements perception, decision-making, memory, and action modules
- External Service Integration:
- Google Workspace (Gmail, Google Drive, Google Sheets)
- Web scraping and content extraction
- DuckDuckGo search integration
- Real-time Communication:
- Telegram Bot interface
- Server-Sent Events (SSE) for live updates
- Core Components:
- Agent loop management
- Session handling
- Context management
- Strategic decision making
🏗️ Project Structure
├── agent.py # Main agent entry point
├── core/ # Core agent components
│ ├── context.py # Context management
│ ├── loop.py # Main agent loop
│ ├── session.py # Session handling
│ └── strategy.py # Strategic decision making
├── modules/ # Cognitive modules
│ ├── action.py # Action execution
│ ├── decision.py # Decision making
│ ├── memory.py # Memory management
│ ├── model_manager.py # Model management
│ ├── perception.py # Input processing
│ └── tools.py # Tool definitions
├── config/ # Configuration files
│ ├── models.json # Model configurations
│ └── profiles.yaml # MCP server profiles
└── mcp_server_*.py # MCP server implementations
🚀 Getting Started
Prerequisites
- Python 3.11+
- UV package manager
- Telegram Bot Token (for bot functionality)
- Google Cloud credentials (for Google Workspace integration)
Installation
1. Clone the repository:
git clone <repository-url>
cd <repository-name>
2. Create and activate a virtual environment:
uv venv
venv\Scripts\activate # On Mac: source venv/bin/activate
3. Install dependencies using UV:
uv sync
4. Set up environment variables:
- Create .env with Gemini API key and Telegram Bot token.
- Generate credentials.json using Google OAuth client.
Configuration
1. Configure MCP servers in config/profiles.yaml
2. Set up model configurations in config/models.json
3. Configure Google Cloud credentials:
- Place credentials.json in the root directory
- Run the application once to generate token.json
🎮 Usage
Starting the Agent
uv run agent.py
Starting the Telegram Bot Server
uv run telegram_sse_server.py
🛠️ MCP Servers
MCP Server 1: Basic Operations
- Mathematical operations - Image processing - File operationsMCP Server 2: Document Processing
- Document indexing - Semantic search - Content extraction - Image captioningMCP Server 3: Web Integration
- DuckDuckGo search - Web content fetching - Rate-limited requestsMCP Server 4: Google Workspace
- Gmail integration - Google Sheets operations - Google Drive management - F1 standings fetcher (URL scraper)📡 Communication
Telegram Bot
- Command handling - Message processing - Real-time responsesSSE Server
- Real-time event streaming - Client connection management - Event broadcasting🧠 Cognitive Architecture
The agent implements a cognitive architecture with the following modules:
- Perception: Processes input and extracts relevant information
- Memory: Manages state and historical data
- Decision: Makes strategic decisions based on input and context
- Action: Executes decided actions through appropriate tools
📝 License
MIT License
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