claude mcp add semantic-scholar-mcp -- npx -y semantic-scholar-mcp
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
23 ★ · smaniches/semantic-scholar-mcp · read from the repository page · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 23 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository smaniches/semantic-scholar-mcp;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
**A 14-tool Semantic Scholar MCP server for academic research workflows.** Direct access to 200M+ papers from Semantic Scholar — paper search, citation graph traversal, author profiles, and recommendations — from any Model Context Protocol client (e.g., Claude Desktop, Claude Code, Cursor, Cline, Continue, and others). Every release ships **verifiable supply-chain provenance**: Sigstore-signed SLSA build-provenance attestations on the wheel, sdist, and container image; PEP 740 attestations on the PyPI upload; and a CycloneDX SBOM — so you can prove the artifact you installed was built from this repo. See Provenance & supply chain. > Author: **Santiago Maniches** · ORCID 0009-0005-6480-1987 · TOPOLOGICA LLC **Research authorship:** Santiago Maniches independently directs and maintains this project and is the sole scientific author of its research contributions. AI-assisted tools have supported coding, documentation, and internal review; they do not constitute scientific coauthors or independent validation. Semantic Scholar content and reused software and methods are attributed to their respective sources. --- Quick start No API key is needed to start. Set SEMANTIC_SCHOLAR_API_KEY to use your assigned Semantic Scholar quota and avoid the shared unauthenticated pool. Semantic Scholar currently assigns introductory API keys a 1 request/second limit across all endpoints. Claude Desktop, Docker, pip, and remote (Streamable HTTP) setups are in Installation. --- Provenance & supply chain A research tool is only as trustworthy as the chain from its source to the binary you run. Every release of this server ships cryptographically verifiable supply-chain evidence, all generated in CI from the tagged commit: | Guarantee | What it proves | Where it is produced | |---|---|---| | **SLSA build provenance** (wheel + sdist) | the published distributions were built by this repo's publish.yml from the released tag, not hand-uploaded | publish.yml — actions/attest-build-provenance (build job) | | **SLSA build provenance** (container image) | the ghcr.io image digest was built by this repo's docker.yml | docker.yml — actions/attest-build-provenance, push-to-registry (lines 141–147) | | **PEP 740 attestations** | the PyPI upload itself carries Sigstore-backed attestations under Trusted Publishing | publish.yml — attestations: true (publish-pypi job) | | **CycloneDX SBOM** | a machine-readable bill of materials, generated in an unprivileged job from the exact wheel's statically resolved dependency metadata (wheels only, none of it executed), SHA-256-bound to that wheel, then attested against the wheel alone | publish.yml — cyclonedx-py + scripts/release_sbom.py (sbom job) + actions/attest-sbom (attest-sbom job) | | **SHA-pinned Actions** | every CI action is pinned to a commit SHA, so the release pipeline itself cannot silently change | all jobs in .github/workflows/ (e.g. publish.yml, docker.yml) | Verify the wheel and the container image against their attestations with the GitHub CLI: The full supply-chain posture, including the known-limitations list, is in SECURITY.md. This is **release-time** provenance (proving how the artifact was built); the server does not currently attach a per-response receipt to individual API results. --- How it compares There is no public Semantic Scholar MCP standard, so the most useful comparison is against the obvious alternative: calling the Semantic Scholar REST API yourself from an agent. Everything in the right-hand column is plumbing this server already owns and the caller would otherwise reimplement. | | This server | Raw S2 REST API from an agent | |---|---|---| | Tool surface | 14 typed MCP tools (search, retrieval, recommendations, status) | caller composes raw HTTP requests | | Citation graph | both directions (citations and references) in get_paper | manual paging over two endpoints | | Bulk operations | papers (≤500) and authors (≤1000) in one call | caller batches and paginates | | Full-text snippet search | snippet_search with surrounding context | separate endpoint, caller-assembled | | Paper-ID resolution | seven formats — Semantic Scholar ID, DOI, ArXiv, PubMed, Corpus ID, ACL, URL — validated pre-flight (validators.py) | caller normalizes and validates IDs | | Rate limiting | client-side limiter with a conservative S2-compatible authenticated default and configurable assigned quota (client.py) | caller throttles by hand | | Retry / backoff | bounded, jittered retry on 429/502/503/timeout, honors Retry-After (client.py) | caller implements retry |