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JevScout (Claude Code + Codex)

An open-source toolkit that reduces large MCP responses in Claude Code through a PostToolUse hook and maps Codex session requests to reviewed operations: Jev ranks what stays verbatim, and without an API key results pass through unchanged.
Stars
3
Language
TypeScript
License
MIT
Reading time
2 min
Published by
Community
Author
yctimlin
Last verified
Oct 2026

This is one of several Jev listings for the same project. The canonical entry is JevScout — hqman.

Highlights

  • A Claude Code PostToolUse hook semantically ranks large MCP responses, keeps relevant source text verbatim and offers exact local recovery.
  • If Jev is unavailable or uncertain, or no key is set, the original response passes through unchanged; the key is never written to settings.
  • Demo: a 169 KB MCP result answered in 2 turns instead of 5 (-51% time, -42% cost); -38% time, -26% cost across 7 validation tasks.
  • Install adds one hook for mcp__.* tools and a jevscout command, with no skills and no always-on context.
  • Codex operation execution maps session requests to reviewed, fixed repository operations that host code authorizes, executes and verifies.

Quickstart

bash
claude plugin marketplace add yctimlin/JevScout
claude plugin install jevscout@jevscout

Watch out

Grounded in the truncated repository README and GitHub metadata reviewed on 2026-10-15; the README was cut off in the install section, and the demo percentages are the project's own validation across 7 tasks. The condensation path requires Node.js 24+ and a TypeSafe API key.

Questions about this entry

Short answers drawn from the linked project or page.

Reactions & coverage

Posts, threads, and videos about this entry from around the web.

YouTube: Ray Amjad puts Jev inside an agentic coding loop and looks at what it costs to run.

YouTube: RoboNuggets puts Jev to work inside Claude Code.

Reddit: A Claude Code mod replaces the auto-mode classifier with Jev, 2x faster.

From the Jev guides

Original write-ups on what this entry is for.

From the Jev AI model community

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