Package Version MCP Server

The Package Version MCP Server solves a common pain point for developers who rely on AI assistants to write or refactor code: ensuring that the libraries, runtimes, and container images they recommend are current. In modern software stacks, a single outdated dependency can introduce security vulnerabilities or incompatibilities that ripple through an entire project. By exposing a unified API for querying the latest stable releases across multiple ecosystems—Node.js/npm, Python/PyPI, Java/Maven Central, Go Proxy, Swift Packages, AWS Bedrock AI models, Docker Hub, GitHub Container Registry, and even GitHub Actions—the server lets an LLM check a package’s newest version in real time before embedding it into generated code snippets or documentation.

For developers using Claude, Gemini, or other MCP‑enabled assistants, this capability translates into higher quality outputs and reduced manual maintenance. Instead of hard‑coding version numbers or guessing, the assistant can fetch a precise, up‑to‑date tag and embed it automatically. This is especially valuable in continuous integration pipelines where code is automatically scaffolded or updated; the server guarantees that any generated , , , or Dockerfile references the most recent, stable artifact. In addition, the server’s inclusion of AWS Bedrock models and container registries expands its utility beyond language libraries to encompass AI services and deployment artifacts, making it a versatile tool for full‑stack development.

Key features of the server include:

• Multi‑registry support: A single query can target any supported registry, simplifying tooling for polyglot projects.
• Stable release filtering: Only the latest stable versions are returned, avoiding pre‑release or beta artifacts that could break builds.
• Extensibility: The MCP framework allows the server to be easily integrated into existing workflows, whether via command‑line clients, VS Code extensions, or containerized deployments.
• Low overhead: The server runs as a lightweight Go binary and can be launched locally or in Docker, keeping integration simple for teams with varied infrastructure.

Typical use cases span from code generation tools that automatically scaffold new projects to CI/CD systems that audit dependency versions before deployment. For example, a developer could ask the assistant to “create a new Express app with the latest dependencies,” and the server would supply instead of an older cached version. In a security‑focused environment, the server can be queried as part of a pre‑commit hook to ensure no outdated or vulnerable packages slip into the codebase.

Because it centralizes version lookups in a single, consistent API, the Package Version MCP Server stands out as an indispensable component for any AI‑driven development workflow that prioritizes reliability, security, and up‑to‑date dependencies.