by EBISPOT · MCP Server · ★ 106
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 106 |
| Forks | 48 |
| Language | Java |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 55/100 |
| Open Issues | 61 |
| Last Updated | 2026-10-16 |
| Created | 2022-05-25 |
| Platforms | java, mcp |
| Est. Tokens | ~18k |
The Ontology Lookup Service (OLS) is a repository for biomedical ontologies that aims to provide a single point of access to the latest ontology versions. It provides a website, REST API, and MCP server.
Looking for a ols4 alternative? If you're comparing ols4 with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Structural code intelligence for AI agents — semantic search, knowledge graphs, and a built-in MCP server in o
Stop re-explaining yourself to AI. MARM offers persistent memory, cross-agent context sharing, write queues, s
🦀 Prevents outdated Rust code suggestions from AI assistants. This MCP server fetches current crate docs, use
Browser-based RDF/ontology knowledge graph editor — load RDF from files, URLs or SPARQL endpoints; author node
Persistent memory for AI coding agents
🧠 High-performance persistent memory system for Model Context Protocol (MCP) powered by libSQL. Features vect
Explore other popular mcp server tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: