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arthurpanhku/Arthor-Agent

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

A

MCP

arthurpanhku/Arthor-Agent

Added 1 June 2026

#ai-agent #compliance #document-parsing #fastapi #llm #mcp #ollama #openai

Overview

Arthor-Agent is an MCP server for an AI agent that automates cybersecurity document assessment. It parses multiple formats and uses a RAG knowledge base to identify risks, compliance gaps, and remediations in questionnaires and reports.

Best for

Best for
Security teams automating document review and compliance checks

Use cases

  • Automate security questionnaire responses
  • Assess compliance documents for gaps
  • Extract risks and remediations from reports

How to use

Install

pip install -r requirements.txt

Tools exposed

  • LLM_PROVIDER
  • CHROMA_PERSIST_DIR
  • PARSER_ENGINE
  • ENABLE_GRAPH_RAG
  • LANGGRAPH_CHECKPOINT_DIR
  • SSDLC_DEFAULT_PHASES
  • SSDLC_DEFAULT_STAGE
  • MCP_DOCUMENT_ROOTS
  • AGENT_GATEWAY_ENABLED
  • AGENT_GATEWAY_TOKEN
  • AGENT_GATEWAY_PUBLIC_URL
  • AGENT_GATEWAY_ALLOWED_HOSTS
  • AGENT_GATEWAY_ALLOWED_ORIGINS

Tested with

Claude Desktop, Cursor, ChatGPT

Notes

Arthor-Agent is an MCP server for an AI agent that automates cybersecurity document assessment. It parses multiple formats and uses a RAG knowledge base to identify risks, compliance gaps, and remediations in questionnaires and reports.

90 stars on GitHub. Last updated 2026-05-28. Licensed MIT.

Use cases

  • Automate security questionnaire responses
  • Assess compliance documents for gaps
  • Extract risks and remediations from reports

Pros

  • Open source Python implementation on GitHub
  • Multi-format parsing with RAG for context-aware analysis
  • Directly addresses compliance and risk assessment workflows

Cons

  • Low star count (90) indicates limited community adoption
  • Requires setup of MCP server and knowledge base
  • May need customization for specific regulatory frameworks

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Open source Python implementation on GitHub
  • Multi-format parsing with RAG for context-aware analysis
  • Directly addresses compliance and risk assessment workflows

Cons

  • Low star count (90) indicates limited community adoption
  • Requires setup of MCP server and knowledge base
  • May need customization for specific regulatory frameworks
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