aggrete
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- AlicenseNot gradedqualityCmaintenanceEnables businesses to route AI assistant access to files, databases, email and other MCP tools through a policy-enforcing gateway that filters what agents may call, strips secrets and personal data from results, and blocks prompt-injection content. Risky actions such as sending mail are held for human approval on a web page, and every request, decision and redaction is written to a tamper-evident audit log with Prometheus metrics.MIT
- AlicenseNot gradedqualityDmaintenanceActs as an MCP gateway between AI agents and upstream tool servers, evaluating YAML policies on every tool call, injecting real credentials at the last mile, scanning requests and responses for secrets, PII, and prompt injection, and recording each action in a tamper-evident audit log. Also supports HTTP forward-proxy governance with rate limiting, cost tracking, and policy replay against historical audit data.4Apache 2.0
- AlicenseNot gradedqualityCmaintenanceEnables 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

agentguardofficial
AlicenseNot gradedqualityAmaintenanceEnforces policy controls for AI agents, including spend limits, action approvals, kill switch, scoped credentials, dry-run diffs, loop prevention, and auditable hash-chained logs.MIT- AlicenseBqualityAmaintenanceA governance proxy for AI tools — every MCP/agent tool call is policy-gated, secret-redacted, and written to a hash-chained, offline-verifiable audit trail.13MIT
- 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
TDQS
Scored across 12 tools
Each tool maps to a distinct resource or action: HR person-level lookups, finance aggregate views, ops drafting, external web read/write, and policy meta-tools. The domain prefixes and bracketed categories make it easy to tell timecard, leave balance, headcount plan, budget roles, and pay band apart.
All names use a domain__snake_case prefix, which provides a consistent overall structure. However, the action part is mixed: several tools are bare noun phrases (timecard, headcount_plan, pay_band), while others are verb phrases (read_public_post, post_note, start_here) or single verbs (check, scenarios).
Twelve tools is well within the ideal range, and each tool earns its place: data sources across HR, finance, ops, and external web, plus guidance and policy-checking tools. The count is large enough to demonstrate multiple policy scenarios without becoming a sprawling surface.
For a policy-decision demo, the surface is complete: start_here and scenarios orient the agent, check lets it test policy decisions before acting, and the data/web tools cover the described policy cases including redaction, comparing colleagues, individual pay, combination refusals, and the prompt-injection shield. No obvious dead-end workflow or missing operation exists for the stated purpose.