Detectify — MCP Server brings deterministic vuln scanning into AI coding agents
AI relevance: Detectify is launching an MCP Server that plugs professional-grade vulnerability scanning directly into AI coding agents, creating a deterministic verification layer for autonomous development loops — addressing the gap where AI-written code outpaces human security review.
- Detectify AB launched a Model Context Protocol server that exposes its vulnerability scanning engines to AI agents, enabling autonomous finding, patching, and validation of security flaws in real time.
- The "Find & Fix" automation feature hands security findings to AI agents as structured remediation tasks: the agent generates a patch, triggers a Detectify validation scan to confirm the fix, and surfaces results for human review.
- A conversational interface lets users query scan results, monitor asset status, and surface high-severity findings through natural-language prompts.
- Detectify frames the core problem as a determinism gap: LLMs reason probabilistically and don't produce consistent outputs, while scanning engines provide deterministic verification. The MCP Server is positioned as the bridge between the two.
- The server is remotely hosted with lightweight configuration for connecting to preferred AI tools, lowering the barrier for teams to integrate security scanning into agentic coding workflows.
- The launch follows a broader pattern of security vendors releasing MCP servers for AI agents, including Legit Security (June 2025), JFrog (July 2025), and TrojAI (November 2025) — signaling a market shift from human-centric dashboards to agent-addressable tooling.
- CEO Rickard Carlsson: "We aren't competing with the AI's reasoning, we are providing the professional-grade tools that reasoning requires." The company monitors millions of changing domains and aims to bring that scale into agentic workflows.
Why it matters
AI coding agents are shipping code faster than human-led review cycles can track. Security tooling that remains trapped in dashboards checked by humans creates a widening gap between code velocity and security coverage. MCP servers for security tools address this by making scanning, validation, and remediation callable from within autonomous development loops.
The determinism argument is also worth noting: as more security vendors build agent-addressable interfaces, the question shifts from "can agents find vulnerabilities?" to "can agents be trusted to validate their own fixes?" Deterministic scanning engines provide an answer to that question.
What to do
- If your team uses AI coding agents (Claude Code, Codex, Copilot), evaluate whether your current security scanning pipeline is reachable from agent workflows or remains a human-only checkpoint.
- Consider the trust boundary: allowing agents to trigger scans and validate patches means your scanning engine becomes part of your agent's tool chain. Review access controls, scoping, and audit logging for that integration point.
- Watch for the broader pattern: security MCP servers from Legit Security, JFrog, and TrojAI suggest this is becoming a standard integration point for AI-native security tooling.