BlastRadius MCP
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- AlicenseNot gradedqualityBmaintenanceEnables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.1MIT
- AlicenseNot gradedqualityBmaintenanceEnables autonomous agents to run shell and subprocess commands through a guardrail that blocks destructive system mutations, path traversals, and reverse shells. It also adds prompt-injection detection, spend circuit breakers, loop detection, and privacy sanitization so agent execution stays within safe, budgeted bounds.7MIT
- AlicenseAqualityCmaintenanceEnables AI agents to run shell commands, perform sandboxed file operations, and make HTTP requests through zero-trust guards that block command injection, path traversal, and SSRF while redacting secrets from inputs and outputs. Circuit breakers, per-session rate limits, and an append-only audit ledger prevent runaway loops, excessive token spend, and provide post-hoc traceability.5MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to call backend tools under per-agent policy, deciding which tools each agent can see, what arguments it may pass, how often it may call, and which writes wait for human approval. It also redacts secrets and PII from tool results, fences untrusted output against injection, and records every call in a hash-chained audit log.25 npmMIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to securely invoke tools by enforcing identity proof, capability verification, and risk scoring on every request, blocking unsafe calls before they execute.MIT
- AlicenseNot gradedqualityBmaintenanceEnables autonomous agents to enforce financial guardrails by tracking real-time token burn and cost velocity, automatically throttling or freezing execution when budgets are exceeded. It also blocks destructive shell commands, prompt injections, and runaway planning loops while sanitizing outputs before they are returned.7MIT
TDQS
Scored across 6 tools
Each tool has a distinct primary purpose spanning prediction, DLP scanning, posture reporting, policy enforcement, token issuance, and audit verification. There is mild overlap where enforce_policy also scans parameters for DLP and evaluates actions like simulate_action, but the descriptions clarify their respective roles well.
All six tools follow a strict verb_noun pattern (simulate_action, inspect_payload_dlp, get_security_posture, enforce_policy, request_confirmation_token, verify_audit_log). The convention is applied uniformly with no deviations.
Six tools is well-scoped for a security guardrail server, with each tool mapping to a discrete responsibility in the pre-execution safety workflow. No tool feels redundant or missing at the count level.
The surface covers a full guardrail lifecycle: simulation, DLP inspection, policy enforcement, step-up approval, posture reporting, and audit verification. Minor gaps exist such as no tool to view/configure policy definitions or revoke issued tokens, but core workflows are covered.