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
MCP
arthurpanhku/Arthor-Agent
Added 1 June 2026
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_PROVIDEREVIDENCE_CRITIC_ENABLEDEVIDENCE_CRITIC_MAX_CANDIDATESEVIDENCE_CRITIC_MAX_THREATSCHROMA_PERSIST_DIRPARSER_ENGINEENABLE_GRAPH_RAGLANGGRAPH_CHECKPOINT_DIRSSDLC_DEFAULT_PHASESSSDLC_DEFAULT_STAGEMCP_DOCUMENT_ROOTSAGENT_GATEWAY_ENABLEDAGENT_GATEWAY_TOKENAGENT_GATEWAY_TENANT_IDAGENT_GATEWAY_PUBLIC_URLAGENT_GATEWAY_ALLOWED_HOSTSAGENT_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
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
Qdrant
Community
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
LangChain
Community
The agent engineering platform.
microsoft/markitdown
Various
Python tool for converting files and office documents to Markdown.
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