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 deepset-ai · MCP Server · ★ 26.6k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is haystack safe to install? View the security audit →
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
| Stars | 26,579 |
| Forks | 3,160 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 62.9817129585272/100 |
| Open Issues | 158 |
| Last Updated | 2026-09-22 |
| Created | 2019-11-14 |
| Platforms | mcp, python |
| Est. Tokens | ~16k |
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haystack is Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, m. It is categorized as a MCP Server with 26.6k GitHub stars.
haystack is primarily written in Python. It covers topics such as agent-framework, agentic-ai, agentic-rag.
You can find installation instructions and usage details in the haystack GitHub repository at github.com/deepset-ai/haystack. The project has 26.6k stars and 3160 forks, indicating an active community.
haystack is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to haystack on Agent Skills Hub include ragflow, voltagent, sdk-python. 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: