Building the Security Layer
for AI Agents

AI agents are making thousands of tool calls per day through MCP servers — reading files, querying databases, calling APIs. Medusa makes sure sensitive data doesn't leak through the cracks.

The Problem

MCP servers are unmonitored attack surfaces

The Model Context Protocol connects AI agents to tools — filesystem access, database queries, API calls, code execution. Every one of these tool calls is a potential data exfiltration vector.

Without inspection, an AI agent can read your source code, access credentials, copy customer data, and send it anywhere — all within a single MCP session. Prompt injection attacks in server responses make this worse: a malicious tool response can instruct the agent to exfiltrate data silently.

Our Solution

On-Device DLP

A Medusa Model runs directly on the endpoint. Scans every tool call for secrets, PII, financial data, and 7 more categories — without any data leaving the device.

Gateway Proxy

Sits transparently between AI agents and MCP servers. Intercepts every JSON-RPC message in both directions. Block, redact, or coach — your policy, your rules.

Fleet Management

Deploy across your entire organization via MDM. Centralized policy management, real-time fleet health monitoring, and automatic MCP server discovery.

Zero Trust Architecture

HMAC-signed policies, SHA-256 model verification, atomic config writes, file permission hardening. Security isn't a feature — it's the foundation.

10

DLP categories

100%

Detection rate

20/sec

Scanning throughput

12+

MCP clients supported

Our Mission

Make AI agents safe to deploy in enterprise environments by providing real-time visibility and control over every tool call — without compromising performance or requiring data to leave the endpoint.

Ready to secure your MCP infrastructure?