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marcojourney

Security Guard MCP

by marcojourney

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Alternatives to Security Guard MCP

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    • F
      license
      Not graded
      quality
      C
      maintenance
      Enables LLM agents to enforce security policies by authorizing tool calls, scanning for prompt injection, checking memory writes, redacting PII, and accessing audit trails through MCP.
      -
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables secure runtime mediation of tool requests from MCP-connected AI agents, enforcing least-privilege policies, validating intent and inputs, detecting multi-step attacks and information leaks, and supporting explainable decisions, audit trails, and human approval for sensitive actions.
      MIT
    • A
      license
      C
      quality
      D
      maintenance
      Enables secure, zero-trust access to MCP tools through short-lived, signed capability leases that bind tool execution to specific sessions, intents, and constraints. Prevents prompt injection attacks and privilege escalation with dynamic risk scoring, policy enforcement, and tamper-evident audit logging.
      4
      1
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to reach upstream MCP tool servers through a central policy gateway that authenticates each agent, enforces least-privilege and default-deny rules, and applies response obligations such as redaction, inference stripping, PII masking, and truncation. It also records every decision in a tamper-evident, hash-chained audit log that can be verified later.
      Apache 2.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to safely call enterprise tools through a governed MCP gateway with permission enforcement, blast-radius controls, input validation, and a full audit trail for every invocation.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      A security MCP proxy that monitors and blocks data exfiltration between AI agents and their tools by detecting toxic flows (untrusted → sensitive → egress) deterministically with zero LLM calls in the decision path.
      1
      MIT