Cursorは、現代のソフトウェア開発のために設計されたAIファーストのコードエディタです。VS Codeのフォークとして構築され、強力なAI機能を編集体験に直接統合し、開発者が前例のない速度とコンテキスト認識能力でコードベースとチャットし、コードを生成、編集、デバッグできるようにします。
DeepSeek R1の推論能力とClaudeのコード生成能力を、統一されたゼロレイテンシのストリーミングAPIを介して組み合わせた無料のオープンソースツールです。高度なAIコードの理解と生成のために設計されており、開発者に自身のAPIキーを使用したプライベートで高度に設定可能な体験を提供します。
製品概要
Cursor 製品概要
Cursorは、現代のソフトウェア開発のために設計されたAIファーストのコードエディタです。VS Codeのフォークとして構築され、強力なAI機能を編集体験に直接統合し、開発者が前例のない速度とコンテキスト認識能力でコードベースとチャットし、コードを生成、編集、デバッグできるようにします。
DeepClaude 製品概要
DeepSeek R1の推論能力とClaudeのコード生成能力を、統一されたゼロレイテンシのストリーミングAPIを介して組み合わせた無料のオープンソースツールです。高度なAIコードの理解と生成のために設計されており、開発者に自身のAPIキーを使用したプライベートで高度に設定可能な体験を提供します。
Detailed feature comparison
| Feature | Cursor | DeepClaude |
|---|---|---|
| 主要カテゴリー | コード生成 | モデルアグリゲーター |
| 追加日 | 2025-08-02 | 2025-08-03 |
| 価格 | フリーミアム | 無料 |
| 公式サイト | cursor.directory | deepclaude.com |
| 製品タイプ | アプリ | ウェブサイト |
| Performance data | ||
| ユーザー評価 | 未確認 | 未確認 |
| コメント | 0 | 0 |
| 月間訪問数 | 179.4K | 3.5K |
| 月間成長率 | -6.7% | 未確認 |
| お気に入り | 128 | 126 |
| Details | 詳細を見る | 詳細を見る |
Cursor vs DeepClaude monthly traffic
Compare Cursor and DeepClaude by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the Cursor vs DeepClaude monthly traffic comparison, Cursor currently shows 179.4K visits and DeepClaude shows 3.5K; Cursor has about 51.9 times the visible traffic of DeepClaude, an absolute difference of about 175.9K visits. This reflects visible reach, not feature quality or paid users.
Only Cursor has complete third-party traffic details; DeepClaude uses visits recorded inside ToolMage. These scopes cannot estimate market share directly, and on-site views should not be treated as the product’s total website traffic.
Cursor monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 365.8K 月間訪問数
- 2026/1: 329.7K 月間訪問数
- 2026/2: 255K 月間訪問数
- 2026/3: 275.2K 月間訪問数
- 2026/4: 192.2K 月間訪問数
- 2026/5: 179.4K 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 49.77% | 89.3K |
| 🇨🇳China | 22.85% | 41K |
| 🇩🇪Germany | 9.76% | 17.5K |
| 🇻🇳Vietnam | 9.67% | 17.3K |
| 🇦🇷Argentina | 7.95% | 14.3K |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 85.37% | 153.1K |
| 参照元 | 12.45% | 22.3K |
| Eメール | 2.18% | 3.9K |
検索キーワード
DeepClaude monthly traffic:
Latest traffic
Usage comparison
Compare the core capabilities of Cursor and DeepClaude
Cursor Core features
DeepClaude Core features
Use cases
Cursor Use cases
DeepClaude Use cases
Cursor vs DeepClaude:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth Cursor vs DeepClaude comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Cursor is primarily listed under “コード生成”, while DeepClaude is primarily listed under “モデルアグリゲーター”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Primary category (Cursor: コード生成; DeepClaude: モデルアグリゲーター); Product type (Cursor: App; DeepClaude: Website); Pricing (Cursor: Freemium; DeepClaude: Free); Monthly visits (Cursor: 179.4K; DeepClaude: 3.5K); Favorites (Cursor: 128; DeepClaude: 126). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the Cursor vs DeepClaude monthly traffic comparison, Cursor currently shows 179.4K visits and DeepClaude shows 3.5K; Cursor has about 51.9 times the visible traffic of DeepClaude, an absolute difference of about 175.9K visits. This reflects visible reach, not feature quality or paid users.
Only Cursor has complete third-party traffic details; DeepClaude uses visits recorded inside ToolMage. These scopes cannot estimate market share directly, and on-site views should not be treated as the product’s total website traffic.
The current traffic scope is not sufficient for a reliable product ranking. Treat monthly visits as a market-interest signal, then decide using taxonomy, use cases, pricing, and a like-for-like trial rather than reading exposure as product capability.
Product positioning, use cases, and roles
Cursor and DeepClaude currently overlap in shared categories: コードアシスタント、開発者ツール; shared tags: コード生成、デバッグ、開発者ツール. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
Cursor's unique categories/tags are コード生成、AIアシスタント、コードエディター、GPT-4、統合開発環境、JavaScript、プログラミング、Python; DeepClaude's are モデルアグリゲーター、API、Claude、コードアシスタント、コード理解、DeepSeek、オープンソース、Rust. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
What ratings, comments, and favorites can tell you
Cursor has no verified rating, 0 comments, 128 favorites, and 115 likes;DeepClaude has no verified rating, 0 comments, 126 favorites, and 121 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate Cursor first
Put Cursor on the priority trial list when the task aligns with “コード生成” and especially コード生成、AIアシスタント、コードエディター、GPT-4、統合開発環境、JavaScript. This follows recorded positioning and does not imply unlisted capabilities are absent.
Cursor also currently records: pricing is freemium, product type is app, 179.4K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
When to evaluate DeepClaude first
Put DeepClaude on the priority trial list when the task aligns with “モデルアグリゲーター” and especially モデルアグリゲーター、API、Claude、コードアシスタント、コード理解、DeepSeek. This follows recorded positioning and does not imply unlisted capabilities are absent.
DeepClaude also currently records: pricing is free, product type is website, 3.5K on-site monthly views, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
How to validate the recommendation before deciding
The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in Cursor and DeepClaude, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.




