MCP Security Guardrails

Secure your AI tool infrastructure - Real-time monitoring and protection for Model Context Protocol servers

Secure Your MCP Now

// MCP Security API Example

const mcpSecurity = require('sonnylabs-mcp-security');

async function checkRequest(request) // Check request safety

const result = await mcpSecurity.analyze(request);

if (result.isSafe) // If request is safe

return 'Request processed';

else // If threat detected

throw new Error(result.threatDetails);

Security Analysis Result:

Request verified: No threats detected

MCP Session Protected

Production Runtime Protection

Monitors MCP server requests and responses. Detects tool poisoning, context manipulation, prompt injections in tool metadata, and sensitive file access attempts through tool calls. Includes real-time monitoring and logs.

Audit Mode

Detect & log threats

Block Mode

Detect & prevent threats

☠️

Tool Poisoning

Detect attempts to manipulate MCP tool calls and hijack functionality

🧠

Context Manipulation

Identify malicious context window manipulation attacks

💉

Prompt Injections

Catch prompt injection attempts in tool metadata and parameters

📁

Sensitive File Access

Block unauthorized file access through MCP tool calls

📊

Real-time Monitoring

Live dashboard with logs and analytics for all MCP activity

🌐

External Content Scan

Scan external data accessed through MCP tools for threats

How MCP Security Works

Simple Implementation

// Import the security module

import MCPSecurity from 'sonnylabs-mcp-security';

// Initialize with your API key

const security = new MCPSecurity(apiKey);

// Create middleware for Express

const protectMCP = async (req, res, next) // Express middleware

try // Attempt to validate the request

await security.validateRequest(req);

next(); // Continue if valid

catch // Handle security violations

res.status(403).send("Security violation");

Real-time Analysis
MCP Security analyzes every request in real-time, identifying potential threats before they reach your models or tools.
Threat Detection Models
Our security models are specifically trained to detect MCP-specific attacks and vulnerabilities.
Detailed Threat Reports
Get comprehensive information about detected threats, including type, severity, and mitigation recommendations.
Seamless Integration
Integrate with any MCP server or client with just a few lines of code, with minimal latency impact.

Business Outcomes

Full visibility into tool access

See exactly what your AI tools are accessing in real-time

Prevent unauthorized data access

Block attempts to access sensitive data through MCP tool calls

Demonstrate governance and control

Show auditors and customers you have control over AI infrastructure

Meet enterprise security requirements

Satisfy vendor security assessments and compliance needs

Protect Your MCP Ecosystem Today

Get Started with MCP Security

Ready to Secure Your AI Applications?

Get in touch with our team to learn how SonnyLabs can help protect your AI systems