A
licenseNot graded
qualityD
maintenanceEnables web content retrieval and semantic search capabilities through the Jina AI API. Provides tools to fetch content from URLs and perform intelligent web searches with natural language queries.
3
MIT
MCP JinaAI Search Server
by spences10
mcp-jinaai-search
⚠️お知らせ
このリポジトリはメンテナンスされなくなりました。
このツールの機能は、複数の MCP ツールを 1 つの統合パッケージにまとめたmcp-omnisearchで利用できるようになりました。
代わりにmcp-omnisearchを使用してください。
Jina.aiの検索APIをLLMと統合するためのモデルコンテキストプロトコル（MCP）サーバー。このサーバーは、WebからクリーンでLLMに適したコンテンツを取得するために最適化された、効率的で包括的なWeb検索機能を提供します。
Related MCP server: Jina AI Remote MCP Server
特徴
🔍 Jina.ai 検索 API による高度なウェブ検索
🚀 高速かつ効率的なコンテンツ検索
📄 構造を保持したクリーンなテキスト抽出
🧠 LLM向けに最適化されたコンテンツ
🌐 ドキュメントを含むさまざまなコンテンツタイプをサポート
🏗️ モデルコンテキストプロトコルに基づいて構築
🔄 パフォーマンス向上のための設定可能なキャッシュ
🖼️ オプションの画像とリンクの収集
🌍 ブラウザのロケールによるローカリゼーションのサポート
🎯 レスポンスサイズのトークン予算制御
構成
このサーバーはMCPクライアント経由で設定する必要があります。以下に、様々な環境における設定例を示します。
傾斜構成
Cline MCP 設定に以下を追加します:
{
"mcpServers": {
"jinaai-search": {
"command": "node",
"args": ["-y", "mcp-jinaai-search"],
"env": {
"JINAAI_API_KEY": "your-jinaai-api-key"
}
}
}
}WSL 構成の Claude デスクトップ
WSL 環境の場合は、Claude Desktop 構成に以下を追加します。
{
"mcpServers": {
"jinaai-search": {
"command": "wsl.exe",
"args": [
"bash",
"-c",
"JINAAI_API_KEY=your-jinaai-api-key npx mcp-jinaai-search"
]
}
}
}環境変数
サーバーには次の環境変数が必要です。
JINAAI_API_KEY: Jina.ai APIキー（必須）
API
サーバーは、構成可能なパラメータを持つ単一の MCP ツールを実装します。
検索
Jina.ai Readerを使ってウェブを検索し、LLMに適したクリーンなコンテンツを取得します。URLとクリーンなコンテンツを含む上位5件の結果を返します。
パラメータ:
query（文字列、必須）: 検索クエリformat(文字列, オプション): レスポンスのフォーマット ("json" または "text")。デフォルトは "text"no_cache(ブール値、オプション): 最新の結果を得るためにキャッシュをバイパスします。デフォルトはfalseです。token_budget(数値、オプション): このリクエストのトークンの最大数browser_locale(文字列、オプション): コンテンツをレンダリングするためのブラウザのロケールstream(boolean, オプション): ラージページのストリームモードを有効にします。デフォルトは falsegather_links（ブール値、オプション）：レスポンスの最後にすべてのリンクを収集します。デフォルトはfalseです。gather_images(ブール値、オプション): レスポンスの最後にすべての画像を収集します。デフォルトはfalseです。image_caption（ブール値、オプション）：コンテンツ内のキャプション画像。デフォルトはfalseenable_iframe(ブール値、オプション): iframeからコンテンツを抽出します。デフォルトはfalseです。enable_shadow_dom(boolean, オプション): Shadow DOMからコンテンツを抽出します。デフォルトはfalseです。resolve_redirects(ブール値、オプション): 最終URLへのリダイレクトチェーンをたどります。デフォルトはtrueです。
発達
設定
リポジトリをクローンする
依存関係をインストールします:
pnpm installプロジェクトをビルドします。
pnpm run build開発モードで実行:
pnpm run dev出版
変更セットを作成します。
pnpm changesetパッケージのバージョン:
pnpm versionビルドして公開:
pnpm release貢献
貢献を歓迎します！お気軽にプルリクエストを送信してください。
ライセンス
MIT ライセンス - 詳細についてはLICENSEファイルを参照してください。
謝辞
モデルコンテキストプロトコルに基づいて構築
Jina.ai検索APIを搭載
Available Tools
1 toolsearchB
Search the web and get clean, LLM-friendly content using Jina.ai Reader. Returns top 5 results with URLs and clean content.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query | |
| format | No | Response format (json or text) | text |
| no_cache | No | Bypass cache for fresh results | |
| token_budget | No | Maximum number of tokens for this request | |
| browser_locale | No | Browser locale for rendering content | |
| stream | No | Enable stream mode for large pages | |
| gather_links | No | Gather all links at the end of the response | |
| gather_images | No | Gather all images at the end of the response | |
| image_caption | No | Caption images in the content | |
| enable_iframe | No | Extract content from iframes | |
| enable_shadow_dom | No | Extract content from shadow DOM | |
| resolve_redirects | No | Follow redirect chains to final URL |
TDQS
B3.1/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool returns 'clean, LLM-friendly content' and 'top 5 results with URLs and clean content,' which gives some behavioral context. However, it lacks critical information about rate limits, authentication requirements, error conditions, or what constitutes 'clean' content, leaving significant gaps for a tool with 12 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise and front-loaded: a single sentence that communicates the core functionality, method, and output format. Every word earns its place with zero redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 12 parameters and no output schema, the description provides basic purpose and output format but lacks sufficient behavioral context. Without annotations covering safety, limits, or authentication, and with no output schema to explain return values, the description should do more to compensate for these gaps, especially given the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 12 parameters. The description doesn't add any parameter-specific information beyond what's already in the schema descriptions. According to guidelines, when schema coverage is high (>80%), the baseline score is 3 even with no parameter information in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search the web and get clean, LLM-friendly content using Jina.ai Reader.' It specifies the action (search), resource (web content), and processing method (Jina.ai Reader). However, without sibling tools, it cannot demonstrate differentiation from alternatives, preventing a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or contextual constraints. It mentions returning 'top 5 results' but doesn't explain when this limitation is appropriate or when other search tools might be better suited.
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.
1 tool update
v1.0.0- First observed
search
TDQS
B3.2/5.0
Scored across 1 tool
Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'search' has a clear and singular purpose, making it impossible for an agent to misselect among non-existent alternatives.
Naming Consistency5/5
A single tool inherently has perfect naming consistency, as there are no other tools to compare against. The name 'search' follows a simple verb pattern, which is appropriate and unambiguous for its function.
Tool Count2/5
A single tool is too few for a server named 'MCP JinaAI Search Server', which suggests a broader search functionality scope. While the tool covers basic web search, the server lacks additional tools for advanced operations like filtering, pagination, or domain-specific searches, making it feel thin and under-scoped.
Completeness2/5
The server is severely incomplete for a search domain. It only offers a basic search tool without any supporting operations such as refining queries, handling multiple result pages, or accessing search history. This creates significant gaps that could lead to agent failures when more complex search tasks are required.
Maintenance
ActivityInactive
ResponsivenessNo issues
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