MCPSecurity

Scan, Test and Protect the MCP Layer Across the AI Lifecycle

Protectt.ai connects AI agents to tools, databases, and enterprise services. Protectt.ai secures that connection at every stage: MCP Scanner vets servers before adoption, MCP Security Testing red-teams them before deployment, and MCP Proxy enforces policy on live agent-to-tool traffic. One platform, three gates, one audit trail.

What is MCP Security, and Why Does It Need a Lifecycle?

MCP security is the set of controls that keep the Model Context Protocol safe to use: vetting the MCP servers an AI agent connects to, verifying they cannot be exploited, and governing what the agent is allowed to do with them at runtime. A single checkpoint is not enough. A poisoned tool description arrives with the package, an injection flaw is only visible on a running server, and a rug pull happens after the server was trusted. Protection must cover adoption, deployment, and runtime as one continuous posture.

The Problem

The Distributed MCP Attack Surface

The Model Context Protocol connects AI agents to external tools. This connectivity is essential, but it introduces a distributed attack surface. Threats do not stay in one place: poisoned tool descriptions enter via the supply chain, injection flaws exploit active servers, and rug-pull attacks alter trusted tools after deployment. No single point of inspection resolves these distributed risks. Agentic AI requires an end-to-end posture that protects the entire lifecycle.

How It Works

Deployment & Trust

Your Policies, Your Environment

MCP Proxy sits in your path, so it runs where your agents run. Deploy it in your cloud, on your own infrastructure, or fully offline in regulated environments where tool-call data must never leave the network.

The Solution

One Platform Across the MCP Lifecycle

FAQ'S

Got Questions? We got Answers.

What is MCP security?

MCP security is the practice of securing the Model Context Protocol layer that connects AI agents to tools, data, and services: vetting MCP servers before adoption, testing them before deployment, and controlling and auditing what agents do with them at runtime.

What is an MCP gateway, and is MCP Proxy one?

An MCP gateway is an inline layer between AI agents and MCP servers that inspects tool calls, enforces access policy, and logs activity. MCP Proxy is Protectt.ai's MCP security gateway: it allowlists servers, enforces least privilege, detects prompt injection in tool responses, redacts sensitive data, and exports an audit trail.

What is an MCP rug pull?

A rug pull is when a trusted MCP server changes its tools or behavior after you approved it. MCP Security Testing records a known-good baseline, and the platform alerts on server-side changes after approval so previously trusted tools cannot silently turn malicious.