@ydzat/literature-review-mcp
npm
v2.0.0
Source verified
Published by ydzat — publish provenance cryptographically ties this package to that repository. That is proof of origin, not an official vendor package.
面向研究生论文级别文献综述的学术论文管理与分析工具,支持多源学术搜索、智能质量评估、智能压缩、多 LLM Provider、Notion 知识库集成
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 3 = 97. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
| Points | Adoption-risk factor |
|---|---|
| −3 | capability blast radius (moderate) — client exposure if the model is manipulated |
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
Untrusted-input tools ([download_arxiv_pdf, batch_download_pdfs]) co-exist with external-action tools ([export_to_notion_full, export_to_notion_update]). A prompt injection could cause unwanted external actions, though no direct sensitive-data leak path was found.
Evidence: untrusted [download_arxiv_pdf, batch_download_pdfs] → sinks [export_to_notion_full, export_to_notion_update]
Fix: Require confirmation for state-changing/egress actions triggered after processing untrusted content.
Location: flow download_arxiv_pdf → export_to_notion_full
In the server's implementation (`build/sources/dblp.js:76`): A hardcoded outbound call to a fixed external host inside server code is a classic exfiltration/telemetry channel — especially paired with reads of local data. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: const response = await axios.get(`https://dblp.org/rec/${id}.xml`, { timeout: 10000, he
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server build/sources/dblp.js
Each tool and what it can reach — statically extracted from the published source.
batch_download_pdfsingests untrusted inputdownload_arxiv_pdfingests untrusted inputexport_to_notion_fullnetwork egressexport_to_notion_updatenetwork egressbatch_analyze_papersno sensitive capabilitybatch_export_individual_reviewsno sensitive capabilityclear_workdirno sensitive capabilityconvert_to_academic_review_enhancedno sensitive capabilityconvert_to_wechat_articleno sensitive capabilityexport_individual_review_to_mdno sensitive capabilitygenerate_unified_literature_reviewno sensitive capabilityparse_pdf_to_markdownno sensitive capabilityparse_pdf_to_textno sensitive capabilityprocess_arxiv_paperno sensitive capabilitysearch_academic_papersno sensitive capabilitysearch_arxiv_papersno sensitive capabilityCross-tool combinations that form a data-exfiltration primitive (untrusted input → sensitive source → external sink).
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v2.0.0 latest |
A 97/100 | 2 | 1.13.0 | 2026-09-07 |
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
npx mcptrustchecker scan @ydzat/literature-review-mcp --online
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