by qdrant · MCP Server · ★ 78
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. Full audit →
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 | 78 |
| Forks | 9 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 59/100 |
| Open Issues | 1 |
| Last Updated | 2026-10-20 |
| Created | 2025-06-03 |
| Platforms | mcp, node |
| Est. Tokens | ~15k |
n8n-nodes-qdrant This is the official n8n node for interfacing with Qdrant. Qdrant is a vector similarity search engine that provides a production-ready service with a convenient API to store, search, and manage vectors. Installation Follow the installation guide in the n8n community nodes documentation.
These tools work well together with n8n-nodes-qdrant for enhanced workflows:
Looking for a n8n-nodes-qdrant alternative? If you're comparing n8n-nodes-qdrant 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.
Local, LLM-free memory for AI agents. A single offline Rust binary — deterministic and auditable — that learns
Claude forgets everything. This fixes that. 🔗 www.npmjs.com/package/claude-self-reflect
Self-hosted RAG platform for AI document search across GitHub, Notion, Google Drive, local files, and web sour
Dragon Brain — persistent long-term memory for AI agents via MCP (Model Context Protocol). Knowledge graph (Fa
A Modern GUI Interface for Vector Database Management(Supports MCP integration)
Home of the AI workforce - Multi-agent system, AI agents & tools
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: