Jina AI MCP Tools
Jina AI MCP 도구
Jina AI Search Foundation API와 통합되는 MCP(Model Context Protocol) 서버입니다.
기능
이 MCP 서버는 다음 Jina AI API에 대한 액세스를 제공합니다:
Web Reader - r.jina.ai를 사용하여 웹 페이지에서 콘텐츠 추출
Web Search - s.jina.ai 또는 svip.jina.ai를 사용하여 웹 검색 (
--search-endpoint를 통해 구성 가능)
Related MCP server: Jina Web Search MCP
사전 요구 사항
Jina AI API 키 (선택 사항) - 향상된 기능을 위해 https://jina.ai/?sui=apikey에서 무료 API 키를 받으세요.
Node.js - 버전 16 이상
MCP 서버
stdio 전송 사용 (기본값)
다른 프로세스(예: Claude Desktop, VS Code, Cursor)에 의해 생성되는 로컬 통합의 경우:
{
"mcpServers": {
"jina-mcp-tools": {
"command": "npx",
"args": [
"jina-mcp-tools",
"--transport", "stdio",
"--tokens-per-page", "15000",
"--search-endpoint", "standard"
],
"env": {
"JINA_API_KEY": "your_jina_api_key_here_optional"
}
}
}
}HTTP 전송 사용
HTTP를 통해 액세스할 수 있는 원격 서버 배포의 경우:
서버 시작:
# With API key
JINA_API_KEY=your_api_key npx jina-mcp-tools --transport http --host 127.0.0.1 --port 3000
# Without API key (reader tool only, binds to 127.0.0.1 by default)
npx jina-mcp-tools --transport http --port 3000MCP 클라이언트에서 연결:
MCP Inspector:
npx @modelcontextprotocol/inspector→http://localhost:3000/mcpClaude Code:
claude mcp add --transport http jina-tools http://localhost:3000/mcpVS Code:
code --add-mcp '{"name":"jina-tools","type":"http","url":"http://localhost:3000/mcp"}'
CLI 옵션:
--transport- 전송 유형:stdio또는http(기본값: stdio)--host- HTTP 모드에서 바인딩할 호스트/인터페이스 (기본값:127.0.0.1)--port- HTTP 서버 포트 (기본값: 3000, HTTP 전송에만 해당)--tokens-per-page- 페이지 매김을 위한 페이지당 토큰 수 (기본값: 15000)--search-endpoint- 사용할 검색 엔드포인트:standard(s.jina.ai) 또는vip(svip.jina.ai) (기본값: standard)--cache-size- URL 단위의 리더 캐시 크기 (기본값: 50)--help- 내장 CLI 도움말 표시
프록시 환경 변수
아웃바운드 HTTP 요청은 이제 표준 프록시 환경 변수를 준수합니다. 이는 jina_reader, jina_search, jina_search_vip에 적용됩니다.
지원되는 프록시 변수:
HTTP_PROXY,HTTPS_PROXY,ALL_PROXY소문자 변형도 지원됩니다:
http_proxy,https_proxy,all_proxyNO_PROXY/no_proxy를 통해 제외 항목이 존중됩니다.
예시:
HTTPS_PROXY=http://proxy.internal:8080 npx jina-mcp-tools --transport stdio사용 가능한 도구
jina_reader
웹 페이지 콘텐츠를 추출하고 읽습니다.
매개변수:
url- 읽을 URL (필수)page- 페이지 매김된 콘텐츠의 페이지 번호 (기본값: 1)customTimeout- 초 단위의 타임아웃 재정의 (선택 사항)
기능:
대형 문서를 위한 자동 페이지 매김
즉각적인 후속 페이지 요청을 위한 LRU 캐시 (50개 URL)
GitHub 파일 URL은 자동으로 원시 콘텐츠 URL로 변환됨
마크다운 지원 문서/블로그 호스트의 유지 관리되는 허용 목록에 대해 먼저
Accept: text/markdown을 시도한 다음, 가져오기 실패나 빈 응답이 발생하면r.jina.ai로 대체됨
jina_search / jina_search_vip
웹을 검색합니다. 부분적인 콘텐츠를 반환하며, 전체 콘텐츠를 보려면 jina_reader를 사용하세요. API 키가 필요합니다.
등록된 도구는 --search-endpoint에 따라 다릅니다:
jina_search→standard(s.jina.ai, 기본값)jina_search_vip→vip(svip.jina.ai)
매개변수:
query- 검색 쿼리 (필수)count- 결과 수 (기본값: 5)siteFilter- 특정 도메인으로 제한 (예: "github.com")
라이선스
MIT
링크
Available Tools
1 tooljina_readerJina Web ReaderC
Read and extract content from web page.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL of the webpage to read and extract content from | |
| page | No | Page number for paginated content (1-indexed) | |
| customTimeout | No | Override timeout in seconds for slow sites |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as whether it is read-only, rate limits, or error handling. It implies reading but offers no further context.
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 a single sentence with no wasted words. However, it is very minimal and could be expanded slightly without losing conciseness.
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?
The tool is simple (read a URL), but the description lacks details about output format, pagination handling (page parameter), or timeout behavior (customTimeout). It is minimally complete but has gaps.
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 100%, so baseline is 3. The description adds no additional meaning beyond the schema; it does not explain parameter semantics or usage context.
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 'Read and extract content from web page' clearly states the verb and resource, but lacks specificity about what kind of extraction (e.g., full HTML, text only). With no sibling tools to differentiate, it is adequate.
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?
No guidance on when to use this tool versus alternatives or any exclusions. The description does not mention constraints like authentication requirements or site compatibility.
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
v1.2.4- Changed
jina_reader1 field changed- removed
Input schema / additionalPropertiesRemoved value: -false
1 tool update
v1.2.0- First observed
jina_reader
TDQS
Scored across 1 tool
Only one tool exists, so there is no ambiguity or risk of misselection.
The single tool name follows a clear 'jina_reader' pattern, consistent with common conventions.
One tool is too few for a server named 'Jina AI MCP Tools', which suggests a broader scope; a tool for reading web pages alone feels insufficient.
The server provides only a read operation, lacking obvious complementary tools like search, list, or write operations, resulting in significant gaps for a comprehensive AI tools surface.
Maintenance
Related MCP Connectors
Jina AI Reader/Search MCP — turn any URL into clean LLM-ready markdown, plus web search.
Web search, AI agent, and content extraction via You.com APIs
Web search, news, page retrieval, sitemaps, and trending topics through Search1API.
The best web search for your AI Agent
Related MCP Servers
- AlicenseBqualityFmaintenanceEnables efficient web search integration with Jina.ai's Search API, offering clean, LLM-optimized content retrieval with support for various content types and configurable caching.121 npm3MIT
- AlicenseNot gradedqualityDmaintenanceEnables 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.3MIT
- AlicenseNot gradedqualityCmaintenanceProvides web content extraction, search capabilities (web, arXiv, SSRN, images), semantic deduplication, and reranking through Jina AI's Reader, Embeddings, and Reranker APIs.1Apache 2.0
- AlicenseNot gradedqualityDmaintenanceProvides tools for web content extraction, search, embeddings, reranking, and image processing via Jina AI APIs, enabling intelligent data retrieval and analysis.Apache 2.0