Jina AI

Jina AI

Call Jina MCP tools via scripts/mcpcall.py for web content extraction, search, academic research, embeddings-based NLP, and visual capture.

Setup

Requires JINA_API_KEY environment variable (get one at jina.ai/api-key):

export JINA_API_KEY=<key>

Web Reading

read_url

Extract web page content as clean markdown. Supports single URL or array of URLs.

• url (required): URL string or array of URLs
• withAllLinks: extract all hyperlinks as structured data
• withAllImages: extract all images as structured data

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py read_url url:"https://example.com"
${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py read_url url:"https://example.com" withAllLinks:true

parallel_read_url

Read up to 5 URLs in parallel for batch extraction.

• urls (required): array of {url, withAllLinks?, withAllImages?} objects
• timeout: milliseconds (default 30000)

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py parallel_read_url --args '{"urls": [{"url": "https://a.com"}, {"url": "https://b.com"}]}'

Web Search

search_web

Search the web for current information. Supports single query or array of queries for parallel search.

• query (required): search terms (string or array)
• num: max results 1-100 (default 30)
• tbs: time filter — qdr:h (hour), qdr:d (day), qdr:w (week), qdr:m (month), qdr:y (year)
• gl: country code (e.g. cn)
• hl: language code (e.g. zh-cn)
• location: location string (e.g. Shanghai)

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py search_web query:"search terms" num:10
${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py search_web query:"A股量化" gl:cn hl:zh-cn
${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py search_web query:"recent news" tbs:qdr:w

parallel_search_web

Run up to 5 web searches in parallel for broader coverage.

• searches (required): array of {query, num?, tbs?, gl?, hl?, location?}
• timeout: milliseconds (default 30000)

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py parallel_search_web --args '{"searches": [{"query": "topic A"}, {"query": "topic B", "num": 5}]}'

search_images

Search for images across the web (like Google Images). Returns base64 JPEG by default.

• query (required): image search terms
• return_url: set true to get URLs instead of base64
• tbs, gl, hl, location: same as search_web

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py search_images query:"neural network diagram"
${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py search_images query:"logo" return_url:true

Academic Research

search_arxiv

Search arXiv for academic papers in STEM fields.

• query (required): search terms, author names, or topics (string or array)
• num: max results 1-100 (default 30)
• tbs: time filter

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py search_arxiv query:"transformer attention" num:10
${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py search_arxiv query:"reinforcement learning" tbs:qdr:m

parallel_search_arxiv

Run up to 5 arXiv searches in parallel for comprehensive coverage.

• searches (required): array of {query, num?, tbs?}
• timeout: milliseconds (default 30000)

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py parallel_search_arxiv --args '{"searches": [{"query": "topic A"}, {"query": "topic B"}]}'

search_ssrn

Search SSRN for social science, economics, law, finance papers.

• query (required): search terms (string or array)
• num: max results 1-100 (default 30)
• tbs: time filter

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py search_ssrn query:"market microstructure" num:10

parallel_search_ssrn

Run up to 5 SSRN searches in parallel.

• searches (required): array of {query, num?, tbs?}
• timeout: milliseconds (default 30000)

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py parallel_search_ssrn --args '{"searches": [{"query": "topic A"}, {"query": "topic B"}]}'

search_bibtex

Search DBLP + Semantic Scholar, return BibTeX citations.

• query (required): paper title, topic, or keywords
• author: filter by author name
• year: minimum publication year
• num: max results 1-50 (default 10)

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py search_bibtex query:"attention is all you need"
${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py search_bibtex query:"deep learning" author:Hinton year:2020 num:5

PDF & Screenshots

extract_pdf

Extract figures, tables, and equations from PDFs using layout detection.

• id: arXiv paper ID (e.g. 2301.12345)
• url: direct PDF URL
• type: filter by figure, table, equation (comma-separated)
• max_edge: max image edge size in px (default 1024)

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py extract_pdf id:2301.12345
${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py extract_pdf url:"https://example.com/paper.pdf" type:figure

capture_screenshot_url

Capture web page screenshots as base64 JPEG.

• url (required): page URL
• firstScreenOnly: true for viewport only (faster), false for full page
• return_url: true to get URL instead of base64

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py capture_screenshot_url url:"https://example.com"
${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py capture_screenshot_url url:"https://example.com" firstScreenOnly:true

NLP & Embeddings

classify_text

Classify texts into user-defined labels using Jina embeddings.

• texts (required): array of strings to classify
• labels (required): array of label strings
• model: embedding model (default jina-embeddings-v5-text-small)

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py classify_text --args '{"texts": ["great product", "terrible"], "labels": ["positive", "negative", "neutral"]}'

sort_by_relevance

Rerank documents by relevance to a query using Jina Reranker.

• query (required): the query to rank against
• documents (required): array of document texts
• top_n: max results to return

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py sort_by_relevance --args '{"query": "machine learning", "documents": ["doc1 text", "doc2 text"], "top_n": 5}'

deduplicate_strings

Select top-k semantically unique strings from a list.

• strings (required): array of strings
• k: number to return (auto-optimized if omitted)

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py deduplicate_strings --args '{"strings": ["hello world", "hi world", "goodbye"]}'

deduplicate_images

Select top-k visually unique images using CLIP v2 embeddings.

• images (required): array of image URLs or base64 strings
• k: number to return (auto-optimized if omitted)

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py deduplicate_images --args '{"images": ["https://a.com/1.jpg", "https://a.com/2.jpg"]}'

expand_query

Rewrite a search query into multiple expanded variants for deeper research.

• query (required): the query to expand

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py expand_query query:"machine learning optimization"

Utility

primer

Get current session context (time, location, network) for localized responses. No parameters.

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py primer

guess_datetime_url

Guess when a web page was last updated/published.

• url (required): page URL

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py guess_datetime_url url:"https://example.com/article"

search_jina_blog

Search Jina AI's official blog and news.

• query (required): search terms (string or array)
• num: max results 1-100 (default 30)
• tbs: time filter

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py search_jina_blog query:"embeddings" num:10

show_api_key

Show the current Jina API key for this session. No parameters.

${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py show_api_key

Tool Selection Guide

Tips

• Use expand_query before parallel_search_web or parallel_search_arxiv to generate diverse queries for thorough research.
• Parallel variants accept up to 5 items — use them for batch work.
• Set tbs:qdr:w to restrict results to the past week for time-sensitive queries.
• For A-share / Chinese market research, set gl:cn hl:zh-cn on search tools.
• ${CLAUDE_PLUGIN_ROOT}/scripts/mcpcall.py --list jina to see all available tools.