As the MCP ecosystem scales to thousands of community-built servers, the attack surface for AI agents has expanded dramatically. MCP-Scan addresses this emerging threat by providing automated security analysis specifically designed for Model Context Protocol servers. The tool inspects server manifests, tool descriptions, and runtime behavior to detect several classes of attacks: tool poisoning where malicious instructions are embedded in tool descriptions to manipulate LLM behavior, prompt injection through tool outputs, cross-origin escalation where one server's tools gain unauthorized access to another server's resources, and rug pull attacks where initially benign servers are later modified to include malicious functionality.
The scanning process examines both static properties and dynamic behavior of MCP servers. Static analysis checks tool descriptions for hidden instructions, excessive permission requests, and suspicious patterns that might indicate an attempt to influence agent behavior beyond the tool's stated purpose. Dynamic analysis monitors actual tool execution to detect discrepancies between declared and actual behavior, data exfiltration attempts, and unauthorized network access. The tool produces structured security reports with severity ratings and remediation recommendations that help development teams make informed decisions about which MCP servers to trust in their agent deployments.
Invariant Labs, the company behind MCP-Scan, was acquired by Snyk in April 2026, signaling that MCP security has become a mainstream concern for the developer security industry. The acquisition brings MCP vulnerability scanning into Snyk's broader application security platform, enabling organizations to include MCP server analysis in their existing security review workflows. As an Apache-2.0 licensed CLI tool, MCP-Scan can be integrated into CI/CD pipelines to automatically scan MCP server configurations before deployment, providing a security gate for the AI agent supply chain.