PRACTICAL FIELD GUIDE
Plan indexes around real filters and sorting
An index should serve a query the application actually performs. Start with the equality filters and sort order of important screens rather than indexing every column without a workload model.
MCPBackend editorial team · · Examples are illustrative
Put it into practice
- List frequent list requests and identify their filter and sort columns.
- Choose supported indexes that match those access patterns and test representative data.
- Compare read usage and response behavior before adding further indexes.
What this looks like
ILLUSTRATIVE EXAMPLE
A task screen repeatedly filters by status and sorts by creation time. Its index decision should reflect that combined access pattern.
A boundary to keep clear
Indexes consume storage and affect writes. A large collection of unused indexes is not a substitute for understanding the query.
MCPBackend context
MCPBackend stores each project's data in SQLite and exposes supported tables through generated REST endpoints. Use the schema tools and dashboard for supported changes. The design examples here are patterns to adapt, not claims that the API exposes every SQLite feature or arbitrary SQL.
Take the next step
Inspect the current project contract, try the change with disposable data, and verify the result through the same credentials your app will use. Record the expected response and one denied-access case before release.
Sources and further reading
These references explain the underlying protocols and design principles. For supported MCPBackend operations and exact request shapes, inspect your project’s generated API contract.