MCP Tasks

Overview

The MCP Tasks server is a lightweight, AI‑friendly task manager that bridges the gap between large language model assistants and structured to‑do lists. It solves a common pain point for developers: keeping the AI’s task‑management logic separate from the actual data store. By exposing a small set of well‑defined tools—add, remove, move, search, and list—the server lets an assistant operate on tasks without risking accidental edits or deletions of the underlying files. This separation protects project history while still giving the AI full control over task flow.

At its core, the server reads and writes to standard text‑based formats—Markdown, JSON, or YAML—so it can be integrated into any workflow that already uses one of these file types. It automatically persists changes in real time, ensuring the AI’s view is always up‑to‑date. The server also supports multiple task files simultaneously, allowing teams to maintain distinct boards (e.g., sprint backlog, bug tracker) without conflating them.

Key capabilities include:

• Budget‑optimized operations: The tool set is intentionally small (five tools) to reduce AI confusion and minimize LLM API calls. Batch operations, smart defaults, and auto‑WIP limits keep the assistant’s request volume low.
• Advanced filtering: Case‑insensitive text and status search with OR logic, plus ID lookup, let the AI quickly find relevant tasks.
• Intuitive ordering: 0‑based insertion and status‑based filtering give developers fine control over task priority while keeping the assistant’s actions straightforward.
• Safety guarantees: By default, the AI can only add or move tasks; it cannot delete or rewrite existing entries unless explicitly enabled. This protects against accidental data loss.
• Type safety: The server is built in TypeScript with Zod validation, ensuring that malformed requests are caught early and communicated clearly to the AI.

Typical use cases include agile sprint planning, bug triage, or any scenario where a conversational assistant needs to keep track of items without direct file manipulation. For example, a team can ask the AI to “move task 42 to In Progress” or “list all overdue tasks,” and the server will handle the file updates behind the scenes. The assistant can also maintain a dedicated reminders section that it can continuously reference, keeping deadlines visible without manual intervention.

Integration is straightforward: developers add the server to their MCP configuration and reference it in prompts. The AI then uses the exposed tools as if they were native commands, enabling a seamless blend of natural language interaction and precise task management. The MCP Tasks server thus empowers developers to harness AI assistants for productivity while preserving the integrity and structure of their existing task files.