by qdrant · MCP Server · ★ 1.6k
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uvx mcp-server-qdrant
uvx mcp-server-qdrant --transport sseTaken from the project's README on GitHub. Check the security audit before running it.
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 | 1,559 |
| Forks | 309 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 78/100 |
| Open Issues | 85 |
| Last Updated | 2026-09-04 |
| Created | 2024-12-02 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~18k |
mcp-server-qdrant: A Qdrant MCP server The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.
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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: