{"id":"arthurpanhku-docsentinel","name":"DocSentinel","af_score":46.0,"security_score":41.5,"reliability_score":27.5,"what_it_does":"DocSentinel is a Python/FastAPI MCP-ready service that parses security documents (PDF/DOCX/XLSX/PPTX/text), indexes an organization’s security policies into a knowledge base (RAG), and uses configurable LLM backends to generate structured security assessment reports (risks, compliance gaps, and remediation suggestions). It exposes REST endpoints for assessments and knowledge-base operations and includes an MCP server for agent integration.","best_when":"You need repeatable, auditable security assessments across many projects using internal policies and you want to integrate the capability into agent workflows via MCP or into pipelines via REST.","avoid_when":"You cannot control data exposure (documents/policies sent to external LLM providers) or you need guaranteed deterministic outputs and formal compliance certification.","last_evaluated":"2026-03-30T13:47:38.555281+00:00","has_mcp":true,"has_api":true,"auth_methods":["API key via OPENAI_API_KEY (for LLM provider)","Environment-variable configuration for service backends (no explicit user auth described in provided README)"],"has_free_tier":false,"known_gotchas":["LLM backends can produce variable outputs; agents should validate/compare to policy clauses returned by RAG","Document parsing (PDF/DOCX/XLSX/PPTX) quality may vary; agents should expect occasional extraction errors","MCP and REST integration may require correct local file/Chroma path configuration (e.g., CHROMA_PERSIST_DIR)","If using cloud LLMs, document/policy content may be transmitted externally; confirm data-handling expectations before deployment"],"error_quality":0.0}