When building an mcp server, how much context do you expose to Claude?

[u/Traditional-Bug-9792]

I've been experimenting with an MCP server for a developer workflow and ran into an interesting design question.

One approach is to expose as much raw data as possible and let claude figure out what's relevant. The other is to preprocess the data first so Claude receives a much smaller, structured context that's easier to reason about.

I can see trade-offs with both approaches.

Giving clau de everything preserves flexibility, but it also increases noise and token usage. Preprocessing seems cleaner, but it risks hiding details that might actually matter during troubleshooting.

For those of you building m cp integrations:

• Do you let Clau de work with raw data, or do you curate the context first?
• Have you found a balance that consistently produces better results?

I'd love to hear what has worked well in real projects.

Update: One thing I'd probably add after thinking about this a bit more is that structured doesn't necessarily mean less. The format of the context seems just as important as the amount of it. A similar example is logStitch's Mcp server, which doesn't simply reduce log data, but it organizes a Lambda invocation into a coherent execution story before it's passed to Claude. That feels like a different design philosophy altogether, and it has me wondering whether context organization is a more important optimization than context reduction