How does the server interpret natural language?
The server sends the command text to the Google Gemini API, which extracts the intent and parameters (e.g., “add”, “list”, “complete”).
@theatulanand
Basic information
Todo app using mcp server
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"todo-mcp": {
"type": "http",
"url": "http://localhost:3000/sse"
}
}
}Tool list not available yet
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A simple Todo application enhanced with natural language processing using the Google Gemini API, MongoDB for persistence, and MCP (Model Context Protocol) for real-time updates via Server-Sent Events (SSE). Built with a modular MVC architecture using Express.js, it is intended for developers who want to manage todos through plain‑language commands and receive live updates.
Clone the repository, install dependencies, and create a .env file with PORT, MONGO_URI, and GEMINI_API_KEY. Start the server with npm start. Send POST requests to /api/command with a JSON body containing a "command" field (e.g., {"command": "Add a task to buy milk"}). Supported commands include adding, listing, completing, and deleting todos. Connect to /sse for real‑time updates (requires an MCP‑compatible client).
The server sends the command text to the Google Gemini API, which extracts the intent and parameters (e.g., “add”, “list”, “complete”).
Todos are stored in a MongoDB Atlas (cloud) cluster using Mongoose as the ODM.
Connect to the `/sse` endpoint with an MCP‑compatible client. The server pushes SSE events when todos change.
Node.js v18 or higher, a MongoDB Atlas cluster, and a Google Gemini API key (available from Google AI Studio).
Set `PORT`, `MONGO_URI`, and `GEMINI_API_KEY` in a `.env` file in the project root. The server reads these on startup.

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