Semantic Scholar MCP Server provides a bridge between AI assistants and the Semantic Scholar academic research database, enabling paper searches, retrieval of paper/author details, and analysis of citations and references. Built with FastMCP and asynchronous processing, it exposes tools for querying papers by keyword, accessing detailed metadata about specific papers and authors, and exploring citation networks. This implementation is particularly valuable for researchers and academics who need to search and analyze scientific literature without leaving their AI assistant interface.
Cognium trust score
65%
Tier
Scanned
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately.
Last scanned 2026-09-02.
Returns 7 tools: search_skills, get_skill, list_leaderboard, get_trust_breakdown, resolve_composition, plus the ChatGPT-connector search and fetch. Every tool is annotated read-only.
Resolve this skill directly via MCP tools/call get_skill.