Todoms MCP Server

Overview

The Todoms MCP server bridges the gap between AI assistants and a lightweight Todo‑management application. By exposing user authentication and CRUD operations for todos through the Model Context Protocol, it lets conversational agents such as Claude or other MCP‑compatible tools treat a Todo app like any other data source. Developers can therefore embed persistent task management directly into dialogue flows, enabling use cases like “Add a new task to my list while we chat” or “Show me the overdue items from yesterday’s meeting notes.”

At its core, the server implements a set of MCP tools that mirror the endpoints of the underlying REST API. Users can sign up, log in to receive a token, and log out or fetch their own profile. Once authenticated, the assistant can list all todos, retrieve a single item by ID, create one or many tasks in bulk, update existing entries, or delete them. Each tool validates input with Zod schemas to ensure data integrity and communicates with the API via a simple fetch‑based client. This tight coupling means that any changes in the Todo backend are automatically reflected in the assistant’s capabilities without additional client code.

The server is built with TypeScript and Node.js, making it straightforward to integrate into existing JavaScript/TypeScript projects. Its modular architecture—separating API clients, data models, and tool definitions—facilitates rapid extension. Adding a new feature involves updating the schema, extending the API client, and defining an MCP tool, keeping the development cycle short.

Key features

• Authentication flow: Sign‑up, login, logout, and current user retrieval.
• Todo CRUD: List all tasks, fetch by ID, create multiple items at once, update, and delete.
• Validation: Input schemas enforced with Zod to prevent malformed requests.
• MCP integration: Exposes tools via stdin/stdout, ready for any MCP‑compatible assistant.
• Extensibility: Modular design allows developers to add new tools or modify existing ones with minimal friction.

Real‑world scenarios

• Personal productivity: An assistant can add, edit, or remind users about tasks while they converse.
• Team collaboration: Agents can pull shared todo lists, update statuses, or assign tasks during meetings.
• Automation pipelines: Integrate with other services (calendar, email) to create tasks automatically from events or messages.

By providing a ready‑made MCP bridge to a Todo backend, Todoms MCP empowers developers to enrich AI interactions with persistent task management without reinventing authentication or CRUD logic.