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Paper Search (arXiv + Semantic Scholar + OpenAlex) logo

Paper Search (arXiv + Semantic Scholar + OpenAlex)

MCPServings/paper-mcp
0 starsMITUpdated 2026-06-17Community

Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

Paper search, arXiv full-text reading, and citation graphs over arXiv, Semantic Scholar, OpenAlex.

README.md

paper-mcp

<!-- mcp-name: io.github.MCPServings/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)

| Tool | Purpose | |---|---| | 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)

| Tool | Purpose | |---|---| | 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). | Tool | Purpose | |---|---| | 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. | Tool | Purpose | |---|---| | 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 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

| Var | Default | Notes | |---|---|---| | PAPER_MCP_HOST | 127.0.0.1 | | | PAPER_MCP_PORT | 9400 | | | PAPER_MCP_PATH | /mcp | | | SEMANTIC_SCHOLAR_API_KEY | — | optional; raises S2 rate limit. Set via /etc/paper-mcp.env in prod. | | MCP_MAX_PER_HOUR | 300 | Direct-client JSON-RPC POST budget per IP. | | MCP_WORKER_MAX_PER_HOUR | 300 | Trusted reverse-proxy Worker budget per HMAC-derived connection key. Raw keys are not retained. | | MCP_WORKER_SHARED_MAX_PER_HOUR | 2400 | Shared ceiling across all trusted Worker connections. | | MCP_RATE_COOLDOWN_SEC | 300 | Minimum fast-rejection cooldown after a bucket reaches its limit. |

---

Deployment (latex-tools.online)

  • Runs as paper-mcp.service on tencent-us (43.130.32.180), WorkingDirectory /opt/paper-mcp, loopback port 9400.
  • nginx reverse-proxies https://latex-tools.online/mcp127.0.0.1:9400/mcp.
  • Worker-aware buckets activate only when a trusted reverse proxy overwrites X-MCP-Worker after validating the upstream platform. Never pass through a client-supplied value.
  • uvicorn access logging is disabled because legacy MCP clients may put connection keys and profiles in the endpoint URL. The reverse proxy must also log $uri, not $request, for the MCP route.
  • Secrets in /etc/paper-mcp.env (SEMANTIC_SCHOLAR_API_KEY).
  • Runtime systemd/nginx/env files are managed by the tencent-us operations backup, not by this source repository; never commit /etc/paper-mcp.env.

Update flow

This repo is the source of truth. The server runs an independent copy under /opt/paper-mcp (not auto-synced): ```bash

edit here → push → deploy the complete canonical Python package

rsync -a --delete paper_mcp/ tencent-us:/opt/paper-mcp/paper_mcp/ ssh tencent-us 'systemctl restart paper-mcp' ssh tencent-us 'curl -s -o /dev/null -w "%{http_code}\n" http://127.0.0.1:9400/mcp' # 406 = healthy (needs JSON-RPC handshake) ```

Production parity verified on 2026-07-23: main@07f6bbe8622aa063f56ee222a40d19c5d4264048 matches all 12 deployed Python source files byte-for-byte. The older copy embedded in latex-tools-deploy/paper-mcp/ is not a deployment source.

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.

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