search-first

To find existing libraries, use a research-first workflow that searches repositories and evaluates maintenance fit before coding. This process clarifies exact capability requirements and compares candidate solutions to recommend whether to adopt, extend, compose, or build custom code.

The best way to compare dependencies for JavaScript and Python integrations is through structured evaluation of candidate solutions. This involves analyzing feature constraints, searching GitHub for existing tools, and evaluating license fit to determine whether to adopt or build.

Whether to build a custom MCP server or extend an existing one depends on a structured comparison of candidate solutions. By researching GitHub-based ecosystems and evaluating maintenance fit, you can decide whether to adopt, extend, compose, or build.

To evaluate open source licenses and maintenance fit before adding a dependency, perform a parallel research sweep of libraries and GitHub repositories. This structured comparison assesses candidate solutions against your constraints and recommends whether to adopt or build.

You should not use existing libraries and instead build custom utility wrappers when structured comparison reveals no candidate solution fits your maintenance, license, or capability constraints. This research-first approach ensures you only build custom when adopt or extend options fail.