by eosho · MCP Server · ★ 236
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Featured in: MCP Database Tools
git clone https://github.com/eosho/langchain_data_agent
Taken from the project's README on GitHub.
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 | 236 |
| Forks | 35 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 72/100 |
| Open Issues | 1 |
| Last Updated | 2026-01-14 |
| Created | 2025-12-22 |
| Platforms | mcp, python |
| Est. Tokens | ~135k |
A natural language to SQL (NL2SQL) platform built on LangGraph and Azure OpenAI. This multi-agent system automatically routes user questions to the appropriate database backend and generates optimized SQL queries and results. Built on top of LangChain's with extended support for Azure AD authentication, Cosmos DB, and built-in dialect validation.
These tools work well together with langchain_data_agent for enhanced workflows:
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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: