広告掲載
MCP.so
ログイン

Task Researcher MCP Server

@tejpalvirk

リポジトリ

基本情報

カテゴリ

生産性

トランスポート

stdio

作者

tejpalvirk

Task Researcher MCP Server について

Researcher for AI Coding that analyzes task complexity and runs deep research (STORM) to decompose complex tasks into subtasks, as an MCP Server or CLI.

Task Researcher MCP Server の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

Task Researcher MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Task Researcher?

Task Researcher is a Python task management system designed for AI-driven development. It integrates in-depth research capabilities using the knowledge-storm library to break down complex projects, generate tasks, and leverage automated research to inform implementation details. It provides both a command-line interface (CLI) and a Model Context Protocol (MCP) server.

How to use Task Researcher?

Install via clone and Poetry, configure a .env file with LLM and search API keys, then use the task-researcher CLI command or run task-researcher serve-mcp to start the MCP server over stdio transport. Clients like Claude Desktop connect by editing their claude_desktop_config.json.

Key features of Task Researcher

  • Parse specifications to generate initial tasks.
  • AI-powered task expansion into subtasks.
  • STORM-based research workflow for complex tasks.
  • Task update and dependency management.
  • Complexity analysis with research hints.
  • Standalone research report generation on any topic.

Use cases of Task Researcher

  • Decomposing software project specifications into executable task lists.
  • Generating detailed subtask breakdowns informed by web research.
  • Updating existing task plans when requirements change.
  • Analyzing and reporting task complexity for project planning.
  • Producing in-depth research reports on technical topics using STORM.

よくある質問

1

What is the difference between `--research` and `--research-hint`?

`expand --research` triggers the full STORM-based workflow, performing live web searches to inform subtasks. `analyze-complexity --research-hint` modifies the prompt to ask the primary LLM to leverage its internal knowledge more deeply without any live search.

2

What are the runtime requirements?

Python 3.10+, an API key for at least one supported LLM provider (e.g., Anthropic, Google Gemini, OpenAI), and the `knowledge-storm` library. A search engine API key is required for the `--research` feature and the `research-topic` command.

3

Where does the task data live?

Task data is stored locally in a `tasks/tasks.json` file following Pydantic models. The file includes a meta section and a list of task objects with dependencies, phases, and subtasks.

4

How are API keys configured?

All credentials are set in a `.env` file. Required variables include `LLM_MODEL`, the provider's API key (e.g., `ANTHROPIC_API_KEY`), `STORM_RETRIEVER`, and the corresponding search API key (e.g., `BING_SEARCH_API_KEY`).

5

What transport does the MCP server use?

The MCP server uses stdio transport by default. It exposes tools like `parse_inputs`, `expand_task`, and `research_topic`, as well as resources such as `tasks://current` and `report://complexity`.

コメント

「生産性」の他のコンテンツ

JobYap

JobYap

JobYap aggregates job postings directly from tech companies' official careers sites and gives every posting a public discussion thread, with salaries, locations and full descriptions.

IBM Engineering Lifecycle Management (ELM) MCP Server

REQUISIS GmbH

IBM Engineering Lifecycle Management (ELM) MCP Server is a remote MCP server available at https://elm-connector.com.

Nextesy MCP

Nextesy MCP is a remote MCP server for clients who use nextesy software. Available at https://nextesy-mcp.com. Not an official app by nextesy.

PaperOffice AI

PaperOffice

Built for companies. Ready for AI agents. PaperOffice is the headless DMS your agent can actually operate: one MCP endpoint to search, read, upload, extract and sign business documents — no UI, no glue code. AI-OCR, invo

42min

42min

Official 42min MCP server: let Claude, ChatGPT, Cursor or any MCP client manage your meeting scheduling. Check availability, find free slots, book, cancel and reschedule meetings, manage recurring series, secret booking

広告掲載