Tama - AI-Powered Task Manager CLI

Tama MCP Server – AI‑Powered Task Management for the Command Line

The Tama server addresses a common pain point in modern software development: turning high‑level product specifications into actionable, traceable work items while keeping the entire workflow in a single terminal. Traditional task‑management tools often require manual entry and lack integration with AI, forcing teams to juggle between documentation, code, and project boards. Tama solves this by embedding AI‑driven parsing and expansion directly into a lightweight CLI, allowing developers to generate structured task trees from plain‑text PRDs and automatically break down complex features into subtasks without leaving the shell.

At its core, Tama exposes a set of RESTful MCP endpoints that mirror familiar CLI commands. These include creating, listing, updating, and deleting tasks, as well as querying status and dependencies. The server’s value lies in its seamless coupling of these CRUD operations with AI services: a DeepSeek model (configured via an OpenAI‑compatible API key) analyzes a or file to produce a hierarchy of tasks, and can further decompose any high‑level task into detailed subtasks on demand. This automation dramatically reduces the manual effort required to translate requirements into development tickets and ensures consistency across the project.

Key capabilities of Tama include:

• Dependency Management – tasks can reference parents, and the server automatically detects circular dependencies, preventing workflow deadlocks.
• Rich Reporting – generate Markdown tables or Mermaid graphs that visualize the entire task graph, making it easy to share progress with stakeholders.
• Code Stub Generation – based on a task’s description, the server can create placeholder files, speeding up scaffolding.
• Next‑Task Suggestion – the server evaluates status and dependency constraints to recommend the most actionable task, helping teams stay focused.
• Integration Hooks – because Tama follows MCP conventions, it can be plugged into any AI assistant that understands the protocol, allowing chat‑based interfaces to query or mutate tasks without custom adapters.

Real‑world scenarios where Tama shines include agile product teams that iterate rapidly on feature specifications, continuous integration pipelines that need to generate test scaffolds from PRDs, and solo developers who prefer a single terminal workflow over juggling multiple tools. By exposing its functionality through MCP, Tama lets AI assistants like Claude or GPT‑4 directly manipulate the task graph: a user can ask, “Show me all pending high‑priority tasks that depend on the authentication feature,” and receive an instant, up‑to‑date list. This tight integration eliminates context switching, keeps documentation and implementation in sync, and ensures that AI‑generated insights are immediately actionable.

In summary, Tama is not just a CLI; it’s an AI‑enhanced task‑management microservice that translates natural language requirements into a structured, dependency‑aware work plan. Its MCP interface makes it a plug‑and‑play component for any AI‑centric development workflow, providing developers with powerful automation while preserving the simplicity and speed of command‑line productivity.