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Agent Safety

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Unified MCP safety server that detects prompt injection (75 patterns), scans LLM outputs for leaked secrets/PII, enforces API cost budgets, and creates signed a

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About

Unified MCP safety server that detects prompt injection (75 patterns), scans LLM outputs for leaked secrets/PII, enforces API cost budgets, and creates signed audit trails. Zero ML dependencies, pure Python.

README

PyPI version License: MIT Python 3.10+

MCP server for AI agent safety. One install gives any MCP-compatible AI assistant access to cost guards, prompt injection scanning, and decision tracing.

Works with Claude Code, Cursor, Windsurf, Zed, and any MCP client.


Install

Claude Code (recommended)

claude mcp add agent-safety -- uvx agent-safety-mcp

Manual (any MCP client)

Add to your MCP config:

{
  "mcpServers": {
    "agent-safety": {
      "command": "uvx",
      "args": ["agent-safety-mcp"]
    }
  }
}

From PyPI

pip install agent-safety-mcp
agent-safety-mcp  # runs stdio server

Tools

Cost Guard — Budget enforcement for LLM calls

Tool What it does
cost_guard_configure Set weekly budget, alert threshold, dry-run mode
cost_guard_status Check current spend vs budget
cost_guard_check Pre-check if a model call is within budget
cost_guard_record Record a completed call's token usage
cost_guard_models List supported models with pricing

Example: "Check if I can afford a GPT-4o call with 2000 input tokens"

Injection Guard — Prompt injection scanner

Tool What it does
injection_scan Scan text for injection patterns (non-blocking)
injection_check Scan + block if injection detected
injection_patterns List all 75 built-in detection patterns across 9 categories

Example: "Scan this user input for prompt injection: 'ignore previous instructions and...'"

Decision Tracer — Agent decision logging

Tool What it does
trace_start Start a new trace session
trace_step Log a decision step with context
trace_summary Get session summary (steps, errors, timing)
trace_save Save trace to JSON + Markdown files

Example: "Start a trace for my analysis agent, then log each decision step"


What this wraps

This MCP server wraps the AI Agent Infrastructure Stack — three standalone Python libraries:

All three: MIT licensed, zero runtime dependencies (individually), pure Python stdlib.

The MCP server adds mcp>=1.0.0 as a dependency for the protocol layer.


Why

AI coding assistants (Claude Code, Cursor, etc.) can now protect the agents they help build — checking budgets, scanning inputs, and tracing decisions — without leaving the IDE.

Built from 8 months of running autonomous AI trading agents in live financial markets.


License

MIT

from github.com/LuciferForge/agent-safety-mcp

Install Agent Safety in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install agent-safety-mcp

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add agent-safety-mcp -- uvx agent-safety-mcp

Step-by-step: how to install Agent Safety

FAQ

Is Agent Safety MCP free?

Yes, Agent Safety MCP is free — one-click install via Unyly at no cost.

Does Agent Safety need an API key?

No, Agent Safety runs without API keys or environment variables.

Is Agent Safety hosted or self-hosted?

A hosted option is available: Unyly runs the server in the cloud, no local setup required.

How do I install Agent Safety in Claude Desktop, Claude Code or Cursor?

Open Agent Safety on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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