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Generate QA datasets & evaluate RAG systems with failure diagnosis. Any LLM.
Generate QA datasets & evaluate RAG systems with failure diagnosis. Any LLM.
RAGScore is an AI/ML evaluation tool with reasonable security practices for its intended purpose. The codebase properly handles external API interactions, uses environment variables for credentials, and includes appropriate logging controls. However, there are concerns about telemetry collection in MCP mode, insufficient input validation on user-supplied endpoints, and potential path traversal vulnerabilities in document processing that should be addressed. Supply chain analysis found 30 known vulnerabilities in dependencies (0 critical, 14 high severity). Package verification found 1 issue.
4 files analyzed · 38 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: OPENAI_API_KEY
Environment variable: ANTHROPIC_API_KEY
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-hzyai-ragscore": {
"env": {
"OPENAI_API_KEY": "your-openai-api-key-here",
"ANTHROPIC_API_KEY": "your-anthropic-api-key-here"
},
"args": [
"ragscore"
],
"command": "uvx"
}
}
}Be the first to review this server!
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