KickJS Query Engine Deep Dive: Filtering, Sorting, Search, and Pagination with MongoDB

KickJS Query Engine Deep Dive: Filtering, Sorting, Search, and Pagination with MongoDB When you're building an API with 60+ endpoints and 10+ list views, you can't afford inconsistency. Some endpoi...

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KickJS Query Engine Deep Dive: Filtering, Sorting, Search, and Pagination with MongoDB

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KickJS Query Engine Deep Dive: Filtering, Sorting, Search, and Pagination with MongoDB When you're building an API with 60+ endpoints and 10+ list views, you can't afford inconsistency. Some endpoints return everything. Some paginate but don't filter. Some sort by createdAt, others by name, and the client has no idea which is which. We solved this in Vibed — a Jira-like task management backend — by building a querying pipeline that flows from URL query strings, through KickJS's ctx.paginate(), into MongoDB helpers, and back out as a standardized paginated response. Every list endpoint works the same way. Here's how the full pipeline works. The Query Pipeline Client request GET /api/v1/projects/abc/tasks?status=eq:open&priority=in:high,critical&sort=-dueDate&search=login&page=2&limit=10 │ ▼ ctx.paginate(fetcher, TASK_QUERY_CONFIG) │ ├── ctx.qs(config) parses the query string │ → filters: [{ field: 'status', operator: 'eq', value: 'open' }, ...] │ → sort: [{ field: 'd

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