Guardrail by NeatProxy is a developer-focused local proxy designed to bring full visibility and control to your AI spending before costs spiral out of control. Created out of real-world frustration with runaway AI agent bills, Guardrail offers a preventative solution for developers building and running AI-driven workflows.

Functioning as a local proxy for tools like Claude Code and Codex, Guardrail breaks down exact spending across system prompts, tool usage, and Model Context Protocol (MCP) servers. Rather than notifying you after a budget has already been exceeded, Guardrail actively intervenes by blocking requests before they execute, ensuring you stay strictly within budget limits.

Pros of Guardrail by NeatProxy

Preemptively blocks requests before blowing your budget, rather than alerting you after the fact
Provides granular spending visibility across system prompts, tools, and MCP servers
Runs as a local proxy tailored for developer workflows using Claude Code and Codex
Prevents unexpected, high API costs when running autonomous AI agents

Cons of Guardrail by NeatProxy

Requires integrating a local proxy into your developer environment
Metadata specifically highlights support for Claude Code and Codex, which may limit broader out-of-the-box model coverage

Frequently Asked Questions

What is Guardrail by NeatProxy?

Guardrail by NeatProxy is a local proxy tailored for developers using AI development tools like Claude Code and Codex. It tracks cost drivers and automatically blocks requests that would exceed your budget.

How does Guardrail prevent budget overruns?

Unlike traditional monitoring tools that alert you after money is spent, Guardrail evaluates costs prior to execution. If a request is about to breach your defined budget, Guardrail blocks it before the call goes through.

What spend details can I see with Guardrail?

Guardrail gives you line-item visibility into where your dollars go, including system prompts, tool calls, and background MCP (Model Context Protocol) servers.