The MCP ecosystem has a trust problem — and scanning source code won't fix it
The Model Context Protocol ecosystem is growing fast. Thousands of MCP servers now offer tools that AI agents call autonomously — executing code, querying databases, moving money, managing infrastructure. Agents are making decisions on behalf of humans, and those decisions depend on servers they've never met.
Recently, a well-circulated analysis scanned roughly 1,800 MCP servers and found security issues in a significant percentage of them. That work was valuable. Static analysis catches real bugs: injection vulnerabilities, missing input validation, insecure defaults.
But here's the question nobody asked: what happens after deployment?
A server can pass every static check and still behave terribly in production — dropping requests, responding with garbage after midnight, degrading quietly over weeks until an agent makes a costly mistake. Static analysis is a snapshot. Production is a film.
