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Check packages for risk and discover capabilities before AI agents use them.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.starloghq/starlog" MCP server from askskill: Run: claude mcp add 'io-github-starloghq-starlog' -- npx -y starloghq
Developers or DevOps teams can vet third-party packages before an AI agent uses them, reducing the chance of introducing risky dependencies. It is especially useful when CVEs, licensing, and maintenance all matter.
When a team is choosing between dependency options, it can use this tool to inspect security and maintenance signals and decide which package is safer. This makes technical selection more transparent and explainable.
If you only know a package name but are unsure what it can do, you can discover its capabilities first and then assess whether it is worth integrating. This fits tool discovery and admission review in AI workflows.
It vets a package before an AI agent uses it, focusing on CVEs, license, and maintenance, and it also supports capability discovery. In other words, it helps with both risk review and understanding what a package may do.
The provided information shows that it checks CVEs, license, and maintenance status. The scope beyond that is not specified in the given material.
The provided material does not include installation steps, runtime requirements, or API key prerequisites. For exact setup details, see the source repository.
Add deterministic security checks, host audits, and diagnostics to AI workflows.
Audit AI agent code for pre-deploy security risks missed by generic SAST.
Search, install, publish, and review security-scanned AI capabilities.
Provides local Git-history memory for coding agents with reverts and annotations.
Verify package safety for AI coding agents and detect supply-chain risks.
Govern API access for AI agents, detecting breaking changes and blocking unsafe calls.