Scrapling Fetch MCP
scrapling-fetch-mcp
AIアシスタントがボット保護されたWebサイトからコンテンツを取得するのを支援します。Scrapling (patchright + curl-cffi) を使用して自動化対策を回避し、クリーンなHTMLまたはMarkdownを返します。
ドキュメントや参考資料の低頻度な取得に最適化されています。大量のスクレイピングやデータ収集を目的とした設計ではありません。
要件: Python 3.10+、uv
Claude Code Skill
最も簡単な利用方法はClaude Codeスキルとして使用することです。インストールすると、Claudeはユーザーが尋ねた際にボット保護されたURLを自動的に取得します。手動コマンドは不要です。
プロジェクトにインストール (推奨 — このプロジェクトのコンテキストでのみ読み込まれます):
git clone --depth=1 https://github.com/cyberchitta/scrapling-fetch-mcp /tmp/scrapling-fetch-mcp
cp -r /tmp/scrapling-fetch-mcp/skills/s-fetch .claude/skills/
cp -r /tmp/scrapling-fetch-mcp/skills/s-fetch-setup .claude/skills/
rm -rf /tmp/scrapling-fetch-mcpまたはすべてのプロジェクトにインストール (どこでもコンテキストに読み込まれます):
git clone --depth=1 https://github.com/cyberchitta/scrapling-fetch-mcp /tmp/scrapling-fetch-mcp
cp -r /tmp/scrapling-fetch-mcp/skills/s-fetch ~/.claude/skills/
cp -r /tmp/scrapling-fetch-mcp/skills/s-fetch-setup ~/.claude/skills/
rm -rf /tmp/scrapling-fetch-mcpその後、Claudeに /s-fetch-setup を実行するように依頼してください。ツールとブラウザバイナリ(大容量のダウンロード)がインストールされ、その後自己削除されます。以降は、自然に尋ねるだけで利用可能です:
"Fetch the docs at https://example.com/api"
"Find all mentions of 'authentication' on that page"
"Get me the installation instructions from their homepage"Related MCP server: mult-fetch-mcp-server
Claude Desktop (MCP Server)
すでに /s-fetch-setup を実行済みであれば、ツールはインストールされています。以下の設定に進んでください。
まだの場合は、先にインストールしてください:
uv tool install git+https://github.com/cyberchitta/scrapling-fetch-mcp
uvx --from git+https://github.com/cyberchitta/scrapling-fetch-mcp scrapling install注意: ブラウザのインストールには数百MBのダウンロードが必要であり、初回使用前に完了している必要があります。サーバーがタイムアウトした場合は、数分待ってから再試行してください。
Claude DesktopのMCP設定に以下を追加し、再起動してください:
MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"scrapling-fetch": {
"command": "uvx",
"args": ["scrapling-fetch-mcp"]
}
}
}仕組み
Claudeによって自動的に使用される2つのツール:
ページ取得 — ページネーション対応でページ全体を取得
パターン抽出 — 正規表現に一致するコンテンツを検索
自動的にエスカレーションされる3つの保護レベル:
basic — 高速 (1-2秒)、ほとんどのサイトで動作
stealth — 中速 (3-8秒)、ヘッドレスChromium
max-stealth — 低速 (10秒以上)、完全なブラウザフィンガープリント
制限事項
テキストコンテンツのみ (ドキュメント、記事、参考資料)
大量のスクレイピングや認証が必要なサイトには不向き
パフォーマンスはサイトの複雑さと保護レベルによって異なります
ライセンス
Apache 2.0
Available Tools
2 toolss_fetch_pageA
Fetches a complete web page with pagination support. Retrieves content from websites with bot-detection avoidance. For best performance, start with 'basic' mode (fastest), then only escalate to 'stealth' or 'max-stealth' modes if basic mode fails. Content is returned as 'METADATA: {json}\n\n[content]' where metadata includes length information and truncation status.
Args:
url: URL to fetch
mode: Fetching mode (basic, stealth, or max-stealth)
format: Output format (html or markdown)
max_length: Maximum number of characters to return.
start_index: On return output starting at this character index, useful if a previous fetch was truncated and more content is required.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| mode | No | basic | |
| format | No | markdown | |
| max_length | No | ||
| start_index | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: bot-detection avoidance, performance characteristics of modes, pagination support, output format structure ('METADATA: {json}\n\n[content]'), and truncation handling. It doesn't mention rate limits, authentication needs, or error conditions, but covers most essential operational aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It starts with the core purpose, adds usage guidelines, describes output format, then details parameters in a clear 'Args:' section. Every sentence adds value, though the parameter explanations could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters with 0% schema coverage and no annotations, the description does an excellent job covering the tool's functionality. It explains purpose, usage, behavior, parameters, and output structure. The presence of an output schema means return values don't need explanation. The main gap is lack of error handling or edge case information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides meaningful context for all 5 parameters: explains what 'url' is for, defines 'mode' options and their purpose, specifies 'format' choices, clarifies 'max_length' as character limit, and describes 'start_index' for handling truncation. This adds substantial value beyond the bare schema, though some details like default values are only in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Fetches a complete web page with pagination support. Retrieves content from websites with bot-detection avoidance.' This specifies the verb ('fetches'), resource ('web page'), and key capabilities ('pagination support', 'bot-detection avoidance'). It doesn't explicitly differentiate from sibling tool 's_fetch_pattern', but the purpose is well-defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use different modes: 'For best performance, start with 'basic' mode (fastest), then only escalate to 'stealth' or 'max-stealth' modes if basic mode fails.' This gives clear operational advice and distinguishes between modes based on performance and fallback scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
s_fetch_patternA
Extracts content matching regex patterns from web pages. Retrieves specific content from websites with bot-detection avoidance. For best performance, start with 'basic' mode (fastest), then only escalate to 'stealth' or 'max-stealth' modes if basic mode fails. Returns matched content as 'METADATA: {json}\n\n[content]' where metadata includes match statistics and truncation information. Each matched content chunk is delimited with '॥๛॥' and prefixed with '[Position: start-end]' indicating its byte position in the original document, allowing targeted follow-up requests with s-fetch-page using specific start_index values.
Args:
url: URL to fetch
search_pattern: Regular expression pattern to search for in the content
mode: Fetching mode (basic, stealth, or max-stealth)
format: Output format (html or markdown)
max_length: Maximum number of characters to return.
context_chars: Number of characters to include before and after each match
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| search_pattern | Yes | ||
| mode | No | basic | |
| format | No | markdown | |
| max_length | No | ||
| context_chars | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: bot-detection avoidance capabilities, performance characteristics of different modes, output format details including metadata structure and content delimiters, and how results enable follow-up requests with s_fetch_page. However, it doesn't mention error handling, rate limits, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with purpose first, usage guidance second, output format third, and parameters last. It's appropriately detailed for a complex tool but could be slightly more concise in the output format explanation. Every sentence serves a clear purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, regex matching, multiple modes), no annotations, but with an output schema present, the description provides excellent contextual completeness. It covers purpose, usage guidelines, behavioral details, parameter semantics, and output format - everything needed for effective tool use without needing to explain return values (handled by output schema).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must fully compensate, which it does excellently. The Args section provides clear semantic explanations for all 6 parameters, including practical guidance for 'mode' selection and explaining what 'context_chars' and 'max_length' control. This adds substantial value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Extracts content matching regex patterns from web pages.' It specifies the verb ('extracts'), resource ('content'), and method ('regex patterns'), distinguishing it from the sibling tool s_fetch_page which presumably fetches full pages rather than pattern-matched content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: 'For best performance, start with 'basic' mode (fastest), then only escalate to 'stealth' or 'max-stealth' modes if basic mode fails.' This gives clear when-to-use instructions for mode selection and implicitly suggests basic mode as the default approach.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
4 tool updates
v1.0.0- Added
s_fetch_page - Added
s_fetch_pattern - Removed
s-fetch-page - Removed
s-fetch-pattern
2 tool updates
- First observed
s-fetch-page - First observed
s-fetch-pattern
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: s_fetch_page retrieves entire web pages with pagination support, while s_fetch_pattern extracts specific content matching regex patterns. Their descriptions explicitly differentiate them, with no overlap in functionality that would cause confusion.
Both tools follow a consistent 's_fetch_' prefix pattern with descriptive suffixes ('page' and 'pattern'), maintaining perfect naming consistency. The snake_case convention is applied uniformly across both tool names.
With only 2 tools, the server feels somewhat thin for a web scraping domain that typically requires more operations like navigation, form handling, or session management. While the tools are well-designed, the limited count may restrict agent capabilities for complex scraping tasks.
The tools cover the core web scraping operations of fetching pages and extracting patterns with bot-detection avoidance. However, there are notable gaps for a complete scraping workflow, such as no tools for navigating between pages, handling authentication, managing sessions, or interacting with dynamic content beyond basic fetching.
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