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Add human approval, policy enforcement, and audit logs to AI tool calls.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "actionproxy" yet — see the docs or source repo.
Design an approval policy for my MCP agent: any tool call that deletes data, changes production systems, or accesses sensitive services must require human approval and log the approver and timestamp.
A policy outline for approval and audit logging on MCP tool calls.
Create an audit checklist for AI agent tool calls, including fields to log, approval steps, and policy-blocking scenarios for a workflow using actionproxy.
A compliance-oriented checklist of audit fields and approval flow steps.
Map a human-in-the-loop workflow for an AI assistant using MCP tools: which actions auto-approve, which require human confirmation, and which should be denied outright.
A clear tiered policy and approval workflow recommendation.
Developers or DevOps teams can use it to add human approval before AI agents execute high-risk external tool actions. It fits MCP workflows where sensitive operations must be reviewed before execution.
When teams need to track which tools an AI agent called, whether approval happened, and whether policies were followed, this tool supports audit logging. It is useful in compliance- and traceability-focused environments.
Product or platform teams can use it as a policy gateway for MCP-compatible tool calls, blocking non-compliant requests or routing them for human review. This helps standardize tool governance across different agents.
It is a human approval gateway for MCP-compatible tool calls. It adds policy enforcement and audit logging to AI agent tool usage.
Yes. The description explicitly says it provides a human-in-the-loop approval gateway, meaning some tool calls can be set to require human approval before proceeding.
The provided material does not include installation steps, runtime requirements, or key setup details. For implementation specifics, see the source repository.
Add policy enforcement, human approval, and audit logs to AI agent tool calls.
Enforce policy checks on AI tool calls without exposing system credentials.
Add a local human approval gate that blocks AI agent actions.
Enforce permissions, approvals, sanitization, and audit for AI agent MCP calls.
Monitor, policy-check, and audit every AI agent tool call.
Securely manage API credentials and proxy requests without exposing secrets to agents.