arthurpanhku/DocSentinel
by Various
MCP server for AI agent for cybersecurity: automate assessment of documents, questionnaires & reports. Multi-format parsing, RAG knowledge base,Risks, compliance gaps, remediations
MCP
arthurpanhku/DocSentinel
Added 1 June 2026
Overview
DocSentinel is an MCP server that enables AI agents to automate cybersecurity document assessment. It parses multiple document formats, builds a RAG knowledge base, and identifies risks, compliance gaps, and remediations.
Best for
Best for
Security teams automating document review workflows
Use cases
- Automate security questionnaire reviews
- Extract compliance gaps from policy documents
- Generate remediation recommendations from audit reports
How to use
Install
pip install -r requirements.txt Tools exposed
LLM_PROVIDERCHROMA_PERSIST_DIRPARSER_ENGINEENABLE_GRAPH_RAGLANGGRAPH_CHECKPOINT_DIRSSDLC_DEFAULT_PHASESSSDLC_DEFAULT_STAGEMCP_DOCUMENT_ROOTSAGENT_GATEWAY_ENABLEDAGENT_GATEWAY_TOKENAGENT_GATEWAY_PUBLIC_URLAGENT_GATEWAY_ALLOWED_HOSTSAGENT_GATEWAY_ALLOWED_ORIGINS
Tested with
Claude Desktop, Cursor, ChatGPT
Notes
DocSentinel is an MCP server that enables AI agents to automate cybersecurity document assessment. It parses multiple document formats, builds a RAG knowledge base, and identifies risks, compliance gaps, and remediations.
90 stars on GitHub. Last updated 2026-05-28. Licensed MIT.
Use cases
- Automate security questionnaire reviews
- Extract compliance gaps from policy documents
- Generate remediation recommendations from audit reports
Pros
- Multi-format document parsing
- Integrates with AI agents via MCP protocol
- Open source with Python codebase
Cons
- Limited community adoption (90 stars)
- Requires setup of MCP-compatible AI agent
- RAG knowledge base may need tuning for domain-specific documents
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Multi-format document parsing
- Integrates with AI agents via MCP protocol
- Open source with Python codebase
Cons
- Limited community adoption (90 stars)
- Requires setup of MCP-compatible AI agent
- RAG knowledge base may need tuning for domain-specific documents
Pairs with
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