If you connect 4–5 MCP servers to Claude Code or OpenAI Codex (GitHub, Playwright, Postgres, Notion), their tools/list JSON schemas silently consume 15,000–35,000 tokens on every turn before you even type a prompt.
On top of that, repositories using both Claude Code (CLAUDE.md) and OpenAI Codex (AGENTS.md) or Cursor (.cursor/rules) quickly suffer from rule drift or accidentally include exposed keys / covert prompt injections inside third-party skills.
I just released CtxWise v1.0 (@framy2/ctxwise, Apache-2.0, 100% local, zero API calls, zero telemetry) to inspect and fix all three in <50ms:
text
$ npx @framy2/ctxwise mcp-xray --probe-stdio
CtxWise mcp-xray · 4 MCP servers · 24 tool schemas · ~18,420 tokens/turn
[BLOATED] ~2,840 tok · github/create_or_update_pull_request (19 params)
[BLOATED] ~1,920 tok · playwright/browser_snapshot_dom (15 params)
-> Tree-shaking savings: ~4,760 tokens saved on every single turn
$ npx @framy2/ctxwise agents && npx @framy2/ctxwise sync --compress
CtxWise multi-agent · parity: synced · Claude ~410 tok · Codex ~410 tok
Synced AGENTS.md <-> CLAUDE.md <-> .cursor/rules/ctxwise.mdc (-34% Token Diet)
$ npx @framy2/ctxwise shield --fail-on-risk
[HIGH] .mcp.json:14 — Hardcoded Anthropic API Key (sk-ant-api03-REDACTED)
[HIGH] .claude/skills/helper/SKILL.md:42 — Covert HTML comment prompt injection
Top comments (1)
The per-turn part is what makes it expensive. A bloated schema is not a one-time cost, it is rent you pay on every message in the session.