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princeruhulofficial

mcp-tool-poison-guard

mcp-tool-poison-guard

Production-ready MCP Server that detects and guards against Tool Poisoning & Prompt Injection attacks in MCP tool descriptions and schemas.

Zero external API cost. Pure local computation + heuristics. Built for entrepreneurs and teams who deploy AI agents in enterprise environments and need trust & accountability.

The Problem (Why this exists)

AI agents using MCP can be tricked by "tool poisoning":

  • Malicious instructions hidden inside tool description or inputSchema

  • When the LLM reads the tool list, it follows the hidden commands (exfiltrate secrets, call restricted tools, ignore system prompt)

  • This is a real 2025-2026 attack class (OWASP, Invariant Labs, academic papers)

Most agents blindly trust tool metadata. This MCP server gives your agents (or your CI/CD) the ability to scan, score, and sanitize tools before they are used.

Related MCP server: InjectShield

What this MCP gives your agents

Tool

What it does

scan_tool_description

Score a single tool description for poisoning risk (0-100)

scan_tools_list

Batch-scan a full tools/list response and rank by risk

detect_injection_patterns

List all known injection / poison patterns found

rewrite_safe_description_tool

Generate a cleaned, safe version of a poisoned description

generate_audit_report

Produce a compliance-friendly audit report of a tool set

simulate_poison_attack

Educational: show what a poisoned tool looks like (for testing)

Quick Start

# 1. Clone
git clone https://github.com/princeruhulofficial/mcp-tool-poison-guard.git
cd mcp-tool-poison-guard

# 2. Install
pip install -e .

# 3. Run (stdio – works with Claude Desktop, Cursor, etc.)
python -m mcp_tool_poison_guard

Claude Desktop config example

{
  "mcpServers": {
    "tool-poison-guard": {
      "command": "python",
      "args": ["-m", "mcp_tool_poison_guard"],
      "cwd": "/path/to/mcp-tool-poison-guard"
    }
  }
}

Why entrepreneurs love this

  • Zero ongoing cost – no OpenAI/Anthropic calls, pure Python heuristics

  • Enterprise-ready – audit reports, risk scores, safe rewrites → easier security reviews

  • Protects your brand – stops agents from leaking customer data or doing unauthorized actions

  • Fits Prevalid philosophy – make AI accountable at the infrastructure level

License

MIT

Author

Prince Ruhul – Founder of Prevalid
https://github.com/princeruhulofficial

A
license - permissive license
-
quality - not tested
B
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

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Related MCP Connectors

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