task_researcher

task_researcher

3
ai_chatbotknowledge_and_memorydeveloper_tools

Task Researcher is a Python-based task management system designed for AI-driven development, leveraging integrated research capabilities. It breaks down complex projects into manageable tasks with automated research to inform implementation details, supporting both CLI and MCP server use.

Task Researcher

A Python task management system for AI-driven development featuring in-depth research capabilities. It allows for breaking down complex projects, generating tasks, and conducting automated research. The package provides both a command-line interface (CLI) and a Model Context Protocol (MCP) Server.

Core Features

  • Parse inputs to generate initial tasks from specification files.
  • Break down tasks into subtasks using AI.
  • Use the STORM-powered research option for complex tasks.
  • Update tasks based on new requirements.
  • Analyze task complexity and generate reports.
  • Manage and fix dependencies.
  • Generate task files and standalone research reports.

Requirements

  • Python 3.10+
  • LLM API key set in a .env file.
  • knowledge-storm library.
  • Optional mcp library for MCP server use.

Installation

  1. Clone the repository.
  2. Install dependencies using Poetry.
  3. Configure the environment by setting API keys and model configurations.

Usage Command Line Interface (CLI)

  • Use the task-researcher command for various operations like parsing inputs, expanding tasks, analyzing complexity, validating dependencies, etc.

MCP Server

  • Can run as an MCP server for exposing functionalities to MCP clients like Claude Desktop.
  • Connect from clients using appropriate settings and commands.