A multi-agent AI system for conversational data analysis — built with LangGraph, MCP, and RAG
- capability exposure inferred + 16
- recent drift inferred + 20
- tool safety inferred + 5
- trust mitigators mixed − 3
inferred mixed
The A–E grade is our heuristic synthesis — a "review this" prompt, not a verdict. Each factor is tagged by what backs it: attested (a verifiable record), reported (a third party's claim), or inferred (our own heuristic, e.g. permissions). See methodology.
graded 4m ago · see ecosystem CVEs →
- B · 30 → C · 38
- A · 0 → B · 30
No known CVEs for this server.
- medium dangerous code
dynamic exec: eval()/exec()
analyzed commit 1cb6784 · analyzer v28 · 1d ago
danger signals1
- dynamic code execution eval()/exec() rit-ops14-nexus-analyst-1cb6784/mcp_server/server.py :81
exec(code, safe_globals)
- recent drift +20 capability drift →
[](https://mcpobservatory.com/servers/github:rit-ops14/nexus-analyst/security) Heuristic, inferred signals — false positives (legitimately powerful tools, forks, language ports) are expected. Treat each as "review this", not a verdict. See the ecosystem-wide picture on the security hub, or the fleet security of rit-ops14.