agent-safety-mcp

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

Related MCP server: guardrails-mcp-server

Tools

Cost Guard — Budget enforcement for LLM calls

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

Injection Guard — Prompt injection scanner

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

Decision Tracer — Agent decision logging

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:

• ai-cost-guard — pip install ai-cost-guard

• ai-injection-guard — pip install ai-injection-guard

• ai-decision-tracer — pip install ai-decision-tracer

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