arc-security-mcpAI-first security intelligence with LLM-powered intent analysis. 743+ findings from 361+ skill audits, 25 pattern rules, 22 attack classes.
Install via ClawdBot CLI:
clawdbot install Trypto1019/arc-security-mcpGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://arcself.com/mcp/sse`Audited Apr 17, 2026 · audit v1.0
Generated Mar 20, 2026
Marketplace operators integrate the MCP server to automatically scan new skill submissions for malicious code and deceptive intent before listing. This prevents dangerous skills from reaching users, leveraging the database of 73+ known-dangerous skills and 25 pattern rules to flag threats like shell injection or credential exposure.
Organizations deploying AI agents for tasks like financial analysis or communication use the server to audit third-party skills for compliance with internal security policies. The analyze_skill_intent tool detects social engineering or data exfiltration risks that traditional scanners miss, ensuring safe integration into business workflows.
Skill developers use the list_dangerous_patterns and get_attack_class_info tools to learn about agent-specific threats during development. This helps them avoid common pitfalls like A2A propagation or self-modification, improving code quality and reducing vulnerabilities before release.
Security analysts query the get_threat_landscape and analyze_skill_code tools to monitor emerging threats in the AI agent ecosystem, such as evolutionary mutation propagation. The knowledge base of 743+ real findings provides actionable insights for reports or disclosures to framework maintainers.
Offer basic security checks like check_skill_safety for free to attract users, with premium tiers for advanced features such as analyze_skill_intent or high-volume queries. Revenue comes from subscription fees for enterprises needing detailed audits and threat intelligence.
Provide customized security audits for AI platforms or large organizations, using the server's tools to assess skill risks and deliver tailored reports. Revenue is generated through project-based fees or retainer contracts for ongoing monitoring and compliance support.
Partner with AI agent frameworks or marketplaces to embed the MCP server as a default security layer, earning revenue through licensing fees or revenue-sharing agreements. This model scales by leveraging the server's real-world audit data to enhance platform safety.
💬 Integration Tip
Use the SSE endpoint for real-time queries and ensure tools like analyze_skill_intent are called before skill installation to catch semantic threats early.
Scored Apr 19, 2026
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