No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by zongmin-yu · MCP Server · ★ 164
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is semantic-scholar-fastmcp-mcp-server safe to install? View the security audit →
Semantic Scholar MCP Server A FastMCP server implementation for the Semantic Scholar API, providing comprehensive access to academic paper data, author information, and citation networks. Project Structure The project has been refactored into a modular structure for better maintainability: This structure: Separates concern
| Stars | 164 |
| Forks | 26 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 78.4980524999121/100 |
| Open Issues | 1 |
| Last Updated | 2026-03-20 |
| Created | 2024-12-25 |
| Platforms | mcp, python |
| Est. Tokens | ~13k |
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semantic-scholar-fastmcp-mcp-server is A FastMCP server implementation for the Semantic Scholar API, providing comprehensive access to academic paper data, author information, and citation networks.. It is categorized as a MCP Server with 164 GitHub stars.
semantic-scholar-fastmcp-mcp-server is primarily written in Python. It covers topics such as agent, fastmcp, llm.
You can find installation instructions and usage details in the semantic-scholar-fastmcp-mcp-server GitHub repository at github.com/zongmin-yu/semantic-scholar-fastmcp-mcp-server. The project has 164 stars and 26 forks, indicating an active community.
semantic-scholar-fastmcp-mcp-server is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to semantic-scholar-fastmcp-mcp-server on Agent Skills Hub include MCP-PostgreSQL-Ops, wcgw, maverick-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: