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BoostSecurity MCP acts as a safeguard preventing agents from adding vulnerable packages into projects. It analyzes every package an AI agent introduces, flags unsafe dependencies, and recommends secure, maintained alternatives to keep projects protected.

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BoostSecurity MCP: Securing Agentic AI Development Workflows

Powered by BoostSecurity

Description

Agentic AI systems can accelerate software delivery by autonomously suggesting or adding code and dependencies. However, without the right safeguards, they can also introduce significant supply chain risks by pulling in third-party packages that:

  • Don’t actually exist (hallucinations)

  • Contain known vulnerabilities, including high or critical severity issues

  • Are end-of-life and no longer supported

  • Are associated with malware or malicious activity

  • Mimic legitimate libraries through typosquatting

BoostSecurity MCP acts as a safeguard for agentic workflows. It analyzes every package an AI agent introduces, flags unsafe dependencies, and recommends secure, maintained alternatives to keep projects protected.

With BoostSecurity MCP, teams can:

  • Block unsafe or malicious packages before they are introduced

  • Verify that dependencies are maintained and supported

  • Receive recommendations for safer alternatives when risks are detected

  • Reduce package-related risks and strengthen the software supply chain

  • Confidently adopt agentic AIβ€”supporting innovation and speed without compromising on security

Supported Languagues and Ecosystems

The following languages and package ecosystems are supported in this release:

  • Python – PyPI

  • Go – Go Modules

  • JavaScript/TypeScript – npm

  • Java – Maven

  • C# – NuGet

Included Tools

BoostSecurity MCP provides the following tools:

  • validate_package: Validates whether a package is safe to use. If the package is unsafe, a recommended alternative is provided.

For Better Results

The BoostSecurity MCP server provides strong instructions and descriptions during connection initialization, encouraging agents to always validate packages before adding to a project.

To ensure best results, add a rule in your AI agent instructing it to validate packages with BoostSecurity MCP. For example:

Always use the BoostSecurity MCP tool `validate_package` to ensure a package is safe before adding it to a project. 
Use the package versions recommended by BoostSecurity.