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 sunanhe · MCP Server · ★ 69
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-medical-mcp-servers safe to install? View the security audit →
Awesome-Medical-MCP-Servers A collection of Medical MCP servers. Awesome-Medical-MCP-Servers What is MCP? Tutorials Servers Acknowledgements What is MCP? MCP is an open protocol that enables AI models to securely interact with local and remote resources through standardized server implementations. This list focuses on production-ready and experimental MCP servers that extend AI capabilities through file access, database connections, API integrations, and other contextual services. Tutorials Model Context Protocol (MCP) Quickstart Setup Claude Desktop App to Use a SQLite Database Servers andybrandt/mcp-simple-pubmed - An MCP server that provides access to PubMed articles through the Entrez API. grll/pubmedmcp - A MCP server that allows to search and fetch articles from PubMed. rikachu225/mcp-pubmed-server - An MCP server implementation for accessing PubMed data with focus on open access content. jackkuo666/medrxiv-mcp-server - A bridge between AI ass
| Stars | 69 |
| Forks | 8 |
| Category | MCP Server |
| License | MIT |
| Quality Score | 54.5218476844449/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-08 |
| Created | 2025-03-23 |
| Platforms | mcp |
| Est. Tokens | ~3k |
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awesome-medical-mcp-servers is A collection of Medical MCP servers.. It is categorized as a MCP Server with 69 GitHub stars.
You can find installation instructions and usage details in the awesome-medical-mcp-servers GitHub repository at github.com/sunanhe/awesome-medical-mcp-servers. The project has 69 stars and 8 forks, indicating an active community.
awesome-medical-mcp-servers is released under the MIT license, making it free to use and modify according to the license terms.
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: