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 cbtw-apac · MCP Server · ★ 55
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is qdrant-loader safe to install? View the security audit →
QDrant Loader 📝 Changelog v1.0.4 - Latest improvements and bug fixes A comprehensive toolkit for loading data into Qdrant vector database with advanced MCP server support for AI-powered development workflows. 🎯 What is QDrant Loader? QDrant Loader is a data ingestion and retrieval system that collects content from multiple sources, processes and vectorizes it, then provides intelligent search capabilities through a Model Context Protocol (MCP) server for AI development tools. Perfect for: 🤖 AI-powered development with Cursor, Windsurf, and other MC
| Stars | 55 |
| Forks | 30 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 54.0612514915435/100 |
| Open Issues | 29 |
| Last Updated | 2026-10-01 |
| Created | 2025-04-06 |
| Platforms | cli, mcp, python |
| Est. Tokens | ~13k |
These tools work well together with qdrant-loader for enhanced workflows:
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qdrant-loader is Enterprise-ready vector database toolkit for building searchable knowledge bases from multiple data sources. Supports multi-project management, automatic ingestion from Confluence/JIRA/Git, intelligen. It is categorized as a MCP Server with 55 GitHub stars.
qdrant-loader is primarily written in Python. It covers topics such as cli-tool, confluence-integration, cursor-ide.
You can find installation instructions and usage details in the qdrant-loader GitHub repository at github.com/cbtw-apac/qdrant-loader. The project has 55 stars and 30 forks, indicating an active community.
qdrant-loader is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to qdrant-loader on Agent Skills Hub include pdf-mcp, skene, ctxvault. 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: