MCP Replies Bill Your Context
Connecting servers is nearly free now — tool descriptions load on demand. The cost moved to responses: whatever a server returns lands in your window whole (warning at 10k tokens, truncation at 25k). A CLI tool lets the agent filter output before it touches context; an MCP server doesn't. Let the agent pick per job — it knows both catalogs.
Why it works
Tool lazy-loading made CONNECTING servers nearly free — the cost moved to RESPONSES. Whatever a server returns lands in your context window whole: there's a warning around 10k tokens and truncation around 25k, and both exist because real servers really do return novels. A CLI tool differs precisely here — the agent can filter its output before it touches context — which is why the right answer per job is 'let the agent pick.'
How to do it
- Keep connected servers to the ones you use — connection is cheap; chatty responses are not.
- Watch for the large-response warning in the transcript; it names the offender.claude code
⚠ tool response: 11,842 tokens (search_records) large responses fill the context window — consider narrowing the query
The warning names the offender; narrow the query or switch tools. - Bulk-output jobs (big exports, long logs) → prefer a CLI tool the agent can filter through.
- Interactive service calls (create a ticket, fetch a record) → the MCP server is perfect.
- When unsure, delegate the choice: 'pick the most token-efficient tool for this.'
- Recurring pipelines deserve an explicit choice once — then record it in CLAUDE.md.
Copy this
This job will produce a lot of output. Choose the most token-efficient route — MCP server or a CLI tool you can filter — and tell me which you picked and why before starting.
What to watch for
- Truncation at the cap is silent-ish: the response just ends. If results feel incomplete after a big tool call, suspect the cap before suspecting the service.
- Uninstalling every server to 'save tokens' optimizes the cheap half — an unused connected server costs almost nothing until it's called.
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