Advertise
MCP.so
Sign In

Tama - AI-Powered Task Manager CLI MCP Server

@Gitreceiver

Repository

Basic information

Category

Developer Tools

License

MIT

Transports

stdio

Author

Gitreceiver

About Tama - AI-Powered Task Manager CLI MCP Server

AI-Powered Task Manager CLI with MCP Server

Tama - AI-Powered Task Manager CLI MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "TAMA-MCP": {
      "command": "uv",
      "args": [
        "venv",
        "-p",
        "3.12"
      ]
    }
  }
}

Tama - AI-Powered Task Manager CLI MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Tama?

Tama is a command-line interface (CLI) tool for task management, enhanced with AI capabilities for task generation and decomposition. It uses an OpenAI-compatible API configured for DeepSeek models to parse product requirements documents (PRDs) and break down complex tasks into manageable subtasks.

How to use Tama?

Install Tama with pip in a Python 3.12 virtual environment, then configure a .env file with your DeepSeek API key and model settings. Run commands like tama add, tama list, tama expand, and tama prd in the terminal. Tama can also be used as an MCP server by running uv --directory /path/to/TAMA_MCP run python -m src.mcp_server.

Key features of Tama

  • Standard task management with dependency tracking
  • AI-powered PRD parsing and task decomposition
  • SQLite database for persistent data storage
  • Git integration for automatic branch and commit creation
  • Code stub generation from task details
  • Dependency cycle detection and visualization
  • Markdown and Mermaid report generation

Use cases of Tama

  • Parse a product requirements document to automatically generate a structured task list
  • Break down high-level tasks into detailed subtasks using AI
  • Track dependencies between tasks and detect circular dependencies
  • Generate placeholder code files based on task descriptions
  • Identify the next actionable task based on status and dependencies

Frequently asked questions

1

What dependencies or runtime does Tama require?

Tama requires Python 3.12 and uses a virtual environment. It depends on the `tama-cli` package, SQLite for storage, and an OpenAI-compatible API key (DeepSeek models are configured by default).

2

How does Tama handle data persistence?

All task data is stored in a local SQLite database, ensuring stable and reliable data operations.

3

Can Tama be used programmatically by other applications?

Yes, Tama can be run as an MCP server over stdio transport, exposing tools like `list_tasks`, `add_task`, and `set_status` for external integration.

4

Does Tama support any shell auto‑completion?

Yes, you can set up shell auto‑completion by running `tama --install-completion`.

5

What AI models does Tama use?

Tama is configured to use DeepSeek models through an OpenAI-compatible API. The configuration requires a `DEEPSEEK_API_KEY` and optionally sets general and reasoning model names.

Comments

More Developer Tools MCP servers

Vibgrate MCP

Vibgrate

Query your team's drift, vulnerability, and migration data from any AI assistant. Vibgrate MCP connects Cursor, Claude, ChatGPT, Windsurf, or VS Code to Vibgrate Cloud: 51 tools for DriftScores, CVEs and EOL runtimes, up

3

Moxie Docs

Jackalope-Dev

Automated codebase documentation for GitHub: searchable docs, MCP context for AI agents, doc drift detection, and Friday Cleanup PRs.

1

CircleCI MCP Server

CircleCI

Manage CI/CD pipelines, debug failed builds, and optimize test suites directly from your AI agents - no terminal required. The CircleCI MCP Server is a remote server hosted by CircleCI that connects AI tools and agents

PubShip

pubship

Open-source MCP server for Google Play developer workflows. Runs locally with your own credentials.

Foremerge

naw103

Catch intent conflicts before code conflicts. The open-source coordination protocol for coding agents, built above Git.

50
Advertise