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DeepRe - AI駆動の深い調査レポート生成ツール MCP Server

@hirokidaichi

リポジトリ

基本情報

カテゴリ

その他

ライセンス

MIT

トランスポート

stdio

作者

hirokidaichi

DeepRe - AI駆動の深い調査レポート生成ツール MCP Server について

local mcp server perplexity

DeepRe - AI駆動の深い調査レポート生成ツール MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "deepre": {
      "command": "deno",
      "args": [
        "task",
        "install"
      ]
    }
  }
}

DeepRe - AI駆動の深い調査レポート生成ツール 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 DeepRe - AI駆動の深い調査レポート生成ツール?

DeepRe - AI駆動の深い調査レポート生成ツール is a Deno-based CLI tool that automatically generates in-depth research reports on a specified theme. It leverages the Google Gemini AI API to iteratively collect and evaluate information until sufficient quality is reached, then produces a comprehensive report in Markdown format. The tool is designed for users who need systematic, automated research on any topic, with full Japanese language support.

How to use DeepRe - AI駆動の深い調査レポート生成ツール?

Install globally with deno task install, then run deepre "調査テーマ". Optionally specify an API key with -k, output directory with -o (default ./research), Gemini model with -m (default gemini-2.0-flash), and iteration count with -i (default 10). The API key can also be set via the GEMINI_API_KEY environment variable. Development tasks include deno task deepre for running in dev mode and deno task check-all for linting, type checking, formatting, and tests.

Key features of DeepRe - AI駆動の深い調査レポート生成ツール

  • Iterative research process with automatic quality evaluation
  • Integrates with Gemini 2.0 AI models for advanced search and analysis
  • Automatically generates an optimal research plan from a theme
  • Full Japanese language support for themes and output
  • Produces formatted Markdown reports

Use cases of DeepRe - AI駆動の深い調査レポート生成ツール

  • Preliminary research for academic projects
  • Market trend and competitive analysis
  • Technology trend investigation
  • In-depth information gathering on specific topics

よくある質問

1

What runtime and API key are required?

Deno runtime is required, along with a Google Gemini API key. The key can be passed via the `GEMINI_API_KEY` environment variable or the `-k` command-line option.

2

What is the default model and iteration count?

The default Gemini model is `gemini-2.0-flash` and the default iteration count is 10. You can override both with the `-m` and `-i` flags respectively.

3

What output format does DeepRe produce?

Reports are output as formatted Markdown files. The default output directory is `./research`, configurable with the `-o` flag.

4

Does DeepRe support Japanese?

Yes, it fully supports Japanese for both setting themes and generating output. The README and usage examples are also in Japanese.

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