agenite
Agenite is a modern, modular framework for building AI agents using TypeScript. It emphasizes type safety and is designed to enhance the developer experience. It simplifies the creation, composition, and control of agents while offering powerful capabilities.
GitHub Stars
65
User Rating
Not Rated
Favorites
0
Views
21
Forks
9
Issues
2
Installation
Difficulty
IntermediateEstimated Time
10-20 minutes
Requirements
Node.js: 18.0.0 or highernpm: 8.0.0 or higherInstallation
Installation
Prerequisites
Please specify required software and versions:Node.js: 18.0.0 or higher
npm: 8.0.0 or higher
Installation Steps
1. Clone Repository
bash
git clone https://github.com/subeshb1/agenite.git
cd agenite
2. Install Dependencies
bash
npm install
3. Start Server
bash
npm start
Troubleshooting
Common Issues
Issue: Server won't start Solution: Check Node.js version and reinstall dependencies.Configuration
Configuration
Basic Configuration
Claude Desktop Setup
Edit~/.config/claude-desktop/claude_desktop_config.json (macOS/Linux) or
%APPDATA%\Claude\claude_desktop_config.json (Windows):
json
{
"mcpServers": {
"agenite-server": {
"command": "node",
"args": ["server.js"],
"env": {
"API_KEY": "your-api-key"
}
}
}
}
Environment Variables
Set the following environment variables as needed:bash
export API_KEY="your-api-key"
export DEBUG="true"
Configuration Examples
Basic Configuration
json
{
"mcpServers": {
"example-mcp": {
"command": "node",
"args": ["server.js"],
"env": {
"PORT": "3000",
"LOG_LEVEL": "info"
}
}
}
}
Examples
Examples
Basic Usage
Here are basic usage examples for the MCP server:Programmatic Usage
javascript
// JavaScript example (Node.js)
const { MCPClient } = require('@modelcontextprotocol/client');
const client = new MCPClient();
await client.connect();
// Execute tool
const result = await client.callTool('toolName', {
parameter1: 'value1',
parameter2: 'value2'
});
console.log(result);
Use Cases
Automating customer support using AI agents.
Enhancing application flexibility by switching between different AI providers.
Streamlining data analysis through integration with databases and file systems.
Utilizing multi-agent systems for distributing and executing complex tasks.