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MCP servers/Search & Web Crawling
mcpservings avatar

Paper Search (arXiv + Semantic Scholar + OpenAlex)

mcpservings/paper-mcp

Three academic search engines behind one MCP interface. You get arXiv with full-text retrieval in markdown, HTML, or raw LaTeX source; Semantic Scholar's citation graph, author lookup, and recommendations; and OpenAlex's 316M cross-discipline catalog with institution and topic filters. The unified search_all tool fans out to all three, deduplicates by DOI, and re-ranks with reciprocal rank fusion. Bonus: image to LaTeX OCR for turning formula or table screenshots back into source code, backed by DeepSeek-OCR and texify models. Reach for this when you need programmatic paper discovery plus the actual manuscript text, not just metadata. Hosted at latex-tools.online or run locally with FastMCP.

last updated
Jun 7, 2026
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Readme

paper-mcp

Remotely-callable MCP server for academic paper search, full-text retrieval & image→LaTeX, served at https://latex-tools.online/mcp.

Three corpora behind one normalized interface:

  • arxiv (default) — search, metadata, and full-text (HTML / markdown / LaTeX source)
  • semanticscholar (alias s2) — the full S2 API surface: citation graph, authors, recommendations, full-text snippets, bulk datasets
  • openalex (alias oa) — 316M all-field works: citation graph, authors with h-index, institutions, topics, influence metrics

Plus a unified search_all that fuses all three corpora, image→LaTeX OCR, and LaTeX lint + PDF→text tooling.


Tools (41)

Generic / source-agnostic (8)

ToolPurpose
search_all(query, max_results=10, sources='arxiv,semanticscholar,openalex')Unified search. Fans out to all three corpora concurrently, de-duplicates the same work (by DOI/title) and re-ranks with Reciprocal Rank Fusion. Each hit carries sources (who found it) + an ids map for follow-up calls. Prefer this for broad lookups.
search_papers(query, source='arxiv', max_results=10, sort_by='relevance')Single-corpus search. arXiv query accepts plain text or field syntax (ti: au: cat:cs.CL abs: + AND/OR).
get_paper(paper_id, source='arxiv')One paper's full record. S2 id accepts S2 id / DOI: / ARXIV: / CorpusId:.
search_by_author(author, source='arxiv')Papers by author, newest first.
list_recent(category, source='arxiv')Latest in a category (arXiv code or S2 field of study).
list_categories(source='arxiv')Common category codes.
read_paper(paper_id, format='markdown')FULL text (arXiv). markdown = body with formulas as $LaTeX$; html = raw LaTeXML page; latex = original manuscript .tex source.
list_paper_sources()Available corpora.

read_paper fetch chain: arxiv.org/html/{id} → ar5iv fallback (markdown/html), or arxiv.org/e-print/{id} tarball main .tex (latex). Formulas are recovered from the LaTeXML alttext invariant.

Medical / evidence-graded (1)

ToolPurpose
search_medical(query, study_types='rct,meta-analysis,systematic-review', year_from=0, max_results=10, fetch_fulltext=True)Clinical literature search. Queries PubMed, filters by research type via Publication-Type tags and re-ranks by the evidence pyramid (meta-analysis / systematic review > RCT > cohort > ...), so real trials surface above high-cited reviews/guidelines that pure-citation ranking floats up. Open-access full text is attached from Europe PMC by PMID. If the type filter yields nothing it auto-relaxes (flagged filter_relaxed). query is English keyword/boolean text — do NL/multilingual query understanding upstream. Backed by NCBI E-utilities + Europe PMC (both free, no key required).

Image → LaTeX (3)

Turn a formula or table image back into LaTeX (e.g. a figure cropped from a paper) without needing your own vision model. Backed by the co-located recognize service (PaddleOCR-VL / DeepSeek-OCR / texify).

ToolPurpose
recognize_formula(image_url=... or image_base64=..., model='deepseek-ocr')Formula image → LaTeX. image_url is downloaded server-side (with SSRF guards). Returns {latex, model, elapsed_ms}.
recognize_table(image_url=... or image_base64=..., model='deepseek-ocr')Table image → LaTeX tabular.
list_ocr_models()Available OCR models (deepseek-ocr, paddleocr-vl, texify).

LaTeX tooling (3)

Companions to the LaTeX/PDF web tools at latex-tools.online — same backends, exposed over MCP.

ToolPurpose
lint_latex(code)Check a LaTeX snippet for errors and return an auto-fixed version. Returns {errors, fixed_code, summary_en, summary_zh, elapsed_ms}.
extract_pdf(pdf_url=... or pdf_base64=..., formula=True, table=True)PDF → clean Markdown/LaTeX text via MinerU (useful for papers with no open-access full text). pdf_url is downloaded server-side (SSRF-guarded). Content-addressed + cached: a recently-seen or small PDF returns content in one call; a fresh PDF (MinerU is GPU-heavy, minutes) returns status='running' + a task_id.
extract_pdf_result(task_id)Fetch an extract_pdf job by task_id. Returns content once status='done'; while 'running', content is null — call again shortly.

OpenAlex (8)

  • Works: get_openalex_work · get_openalex_citations · get_openalex_references · search_openalex_works (filters: year range, open-access, min-citations, institution)
  • Authors/Institutions: search_openalex_authors · search_openalex_institutions
  • Analytics: get_openalex_trends · list_openalex_topics

Semantic Scholar (18)

  • Graph: get_paper_citations · get_paper_references · get_paper_authors
  • Lookup: match_paper_title · autocomplete_papers
  • Bulk: search_papers_bulk (≤1000, sortable, token paging) · get_papers_batch
  • Authors: search_authors · get_author · get_author_papers · get_authors_batch
  • Full-text: search_snippets (search inside paper body)
  • Recommend: recommend_papers_for_paper · recommend_papers_from_examples
  • Datasets: list_dataset_releases · get_dataset_release · get_dataset_download_links · get_dataset_diffs

Layout

paper_mcp/
  server.py            FastMCP server (tool registrations + instructions)
  models.py            normalized Paper model
  aggregate.py         cross-source fusion (dedup + Reciprocal Rank Fusion)
  sources/
    base.py            source registry (get_source / list_sources)
    arxiv.py           arXiv Atom API + read_paper (HTML/markdown/latex)
    semanticscholar.py Semantic Scholar full API surface
    openalex.py        OpenAlex REST API (works/authors/institutions/topics)
    recognize.py       image→LaTeX client over the co-located recognize service
    latextools.py      lint + PDF-extract clients over the latex-tools.online services
pyproject.toml

Run locally

cd paper-mcp
python -m venv .venv && . .venv/bin/activate
pip install -e .
PAPER_MCP_PORT=9400 python -m paper_mcp.server
# MCP endpoint at http://127.0.0.1:9400/mcp (JSON-RPC; a plain GET returns 406)

Env

VarDefaultNotes
PAPER_MCP_HOST127.0.0.1
PAPER_MCP_PORT9400
PAPER_MCP_PATH/mcp
SEMANTIC_SCHOLAR_API_KEY—optional; raises S2 rate limit.
MCP_MAX_PER_HOUR300Direct-client JSON-RPC POST budget per IP.
MCP_WORKER_MAX_PER_HOUR300Trusted reverse-proxy Worker budget per HMAC-derived connection key. Raw keys are not retained.
MCP_WORKER_SHARED_MAX_PER_HOUR2400Shared ceiling across all trusted Worker connections.
MCP_RATE_COOLDOWN_SEC300Minimum fast-rejection cooldown after a bucket reaches its limit.

Notes

  • arXiv calls are politely rate-limited + retried (_USER_AGENT, backoff).
  • read_paper covers ~80%+ of papers via official HTML; older scan-only papers may have no full text.
  • Moved here from the docs repo on 2026-06-07; that copy is gone.

License

MIT © MCPServings. See LICENSE.

Details

Repository
github.com/mcpservings/paper-mcp
Website
latex-tools.online/mcp
Category
Search & Web Crawling
Transport
HTTP
Registry
MCP registry, active

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