AI-assisted development helps teams write code faster, but that speed comes with added security risk. As agents generate more code, they can introduce vulnerabilities, insecure dependencies, or exposed secrets, often before a human reviewer ever sees the change. Security teams are left reviewing more code with the same resources, which makes it harder to catch issues early.
The Datadog Code Security MCP helps teams meet the new security challenges of AI-assisted development by scanning code as it’s generated. Instead of waiting for pull requests or CI pipelines, it analyzes code in real time to detect vulnerabilities, secrets, risky dependencies, and infrastructure misconfigurations. By consolidating checks into a single local MCP server and one authentication flow, teams can apply consistent controls directly in existing workflows without managing multiple tools or added setup.
In this post, we’ll look at how the Datadog Code Security MCP helps teams:
Detect vulnerabilities as code is generatedConsolidate multiple security scans into a single workflow
Detect vulnerabilities as code is generated
