Crux

Keradd4stars

Compression Runtime for Universal eXecution — a 60–95% token reducer for AI coding agents (Claude Code, Cursor, Cline, …). Single Rust binary, SQLite, 11 layers, local-first.

Databases

Install Run on PlugMCP

GitHub

Run on PlugMCP

1# Crux

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
License: Apache-2.0
Last checked: 2026-10-28

Stars: 4
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Crux?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Crux need an API key?

No required environment variable is listed on this record.

What transport does Crux use?

Crux runs locally over stdio.

When was Crux last checked?

Last checked 2026-10-28. Compression Runtime for Universal eXecution — a 60–95% token reducer for AI coding agents (Claude Code, Cursor, Cline, …). Single Rust binary, SQLite, 11 layers, local-first.

From the publisher

Documentation

What is CRUX?

AI coding agents waste tokens re-reading files, echoing redundant tool output, and filling context with verbose prose. CRUX solves this with a layered pipeline that compresses every interaction — before it enters the agent's context window.

One binary. One SQLite database. 12 layers of optimization.

Token costs drop — layered compression over tool descriptions, bash output, file reads, and conversation history.
Context stays lean — per-file read cache with delta replies and structural digests prevent re-reads.
Code is searchable — hybrid BM25 + dense vector + RRF search across code, memory, and conversation chunks.
Execution is safe — Linux rlimits, landlock, and optional seccomp; portable fallback on other platforms.
Output stays clean — comment slop guard strips AI-flavoured prose from source; humanizer rewrites raw AI output into concise text.
Zero telemetry — no cloud, no analytics, no network calls unless you opt in.

Quick start

# Install
cargo install crux

# Register CRUX inside every detected AI agent as an MCP server
crux setup

# Build with the comment-hygiene gate in front of cargo build
crux build --release

# Hybrid code search across the indexed project
crux search "delta cache" --kind code --limit 5

# Scan the workspace for AI-flavoured comments
crux hygiene comments --check

# Rewrite raw AI prose into concise text
crux humanize --mode concise --input "In conclusion, we leverage the robust pipeline."
# → We use the pipeline.

Or build from source: git clone https://github.com/Keradd/crux.git && cd crux && cargo build --release

Why CRUX?

Problem	CRUX solution
Agent re-reads the same files every turn	Layer 4 — read cache with mtime tracking, delta replies, structural digests
Tool descriptions eat context budget	Layer 2 — description shrinker strips redundant prose from MCP tool surfaces
Bash output is verbose and repetitive	Layer 3 — TOML-defined filters (3-tier: static, dynamic, structured)
Code search is slow or cloud-dependent	Layer 6 — hybrid BM25 (porter + trigram) + dense vectors + RRF, all local
Syntax trees are expensive to recompute	Layer 5 — persistent tree-sitter AST graph with cross-file call resolution
AI agents write overly verbose comments	Layer 12 — deterministic scanner, fixer, and stripper for AI-flavoured comments
Raw AI prose wastes tokens	Humanizer — deterministic local rewrite of verbose output into concise text
Unsafe code execution blows up context	Layer 7 — sandboxed subprocess with rlimits, landlock, seccomp

Features

Token optimization — layered compression across all 12 layers.
Context hygiene — read cache, delta replies, structural digests.
Hybrid search — BM25 porter + trigram + dense vectors + RRF.
AST graph — tree-sitter for 6 languages with cross-file call resolution.
Sandboxed execution — Linux rlimits + landlock + seccomp; cross-platform fallback.
Persistent memory — FTS5 + decay-ranked observations with contradiction detection.
Comment slop guard — detect, fix, and strip AI-flavoured source comments.
Output humanizer — rewrite raw AI prose into concise, natural text.
MCP tooling — stdio JSON-RPC server exposing 13 tools, plus description shrinker proxy.
Hygiene-aware build — crux build gates on comment hygiene before cargo build.

Commands

Command	Description
`crux setup`	Register CRUX inside every detected AI agent
`crux init`	Scaffold `.crux/`, `CLAUDE.md`, and project profile
`crux index` / `crux reindex`	Build AST graph and chunk store
`crux search <query>`	Hybrid BM25 + dense + RRF search
`crux find <name>` / `crux impact <symbol>`	Symbol lookup and blast radius
`crux execute --runtime <python\|bash\|node>`	Sandboxed code execution
`crux remember` / `crux recall`	Decay-ranked observation store
`crux bash <cmd>`	Run command through the filter pipeline
`crux hygiene comments --check\|--fix\|--strip`	AI-comment slop guard
`crux humanize --mode <mode>`	Rewrite AI-flavoured prose
`crux build`	Hygiene check + `cargo build`
`crux audit` / `crux stats`	Health snapshot and telemetry
`crux digest` / `crux compact`	Conversation turn-event rollups
`crux mcp` / `crux mcp-shrink`	MCP server or description shrinker proxy

CRUX_HOME overrides ~/.crux. CRUX_PROJECT overrides project-root detection.

Architecture

CRUX is a layered pipeline. Each layer compresses or transforms agent interactions independently:

Input → L1 (Output rules) → L2 (MCP shrink) → L3 (Bash filter) → L4 (Read cache)
         → L5 (AST graph) → L6 (Search) → L7 (Sandbox) → L8 (Memory)
         → L9 (Coach) → L10 (Setup) → L11 (Digest) → L12 (Hygiene)

See docs/ARCHITECTURE.md for the full design.

Documentation

Architecture — goals, tech stack, data model, per-layer internals, security model.
Install — from-source build, --features matrix, per-agent activation.
MCP tools — stdio server, description shrinker, full tool surface.
Humanizer — modes, examples, what it never touches.
Comment Hygiene — scanner, fixer, stripper behaviour.
Contributing — workspace conventions, PR checklist, comment rules.
Changelog — release history.
Examples — scaffolded projects to explore.

Privacy

CRUX is local-first. No cloud backend, no analytics, no update ping. Telemetry lives in a local SQLite database ($CRUX_HOME/db/crux.sqlite, mode 0600) and is only exposed via crux audit / crux stats. The MCP server defaults to stdio; the TCP daemon binds to 127.0.0.1. No network calls happen unless you explicitly opt into a cloud embedder or remote transport.

Secrets handling: docs/ARCHITECTURE.md §14.2.

Development

MSRV: Rust 1.96. CI runs 5 jobs on Ubuntu + stable:

cargo fmt --all -- --check
cargo clippy --workspace --all-targets -- -D warnings
cargo test --workspace --exclude crux-l7-sandbox
RUSTDOCFLAGS="-D warnings" cargo doc --workspace --no-deps

Prefer crux build over cargo build — the hygiene gate runs first. See CONTRIBUTING.md for the full PR checklist.

License

Licensed under MIT OR Apache-2.0 at your option:

Contributions are dual-licensed under the same terms.

Crux

Keradd4stars

Compression Runtime for Universal eXecution — a 60–95% token reducer for AI coding agents (Claude Code, Cursor, Cline, …). Single Rust binary, SQLite, 11 layers, local-first.

Databases

Install Run on PlugMCP

GitHub

Run on PlugMCP

1# Crux

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
License: Apache-2.0
Last checked: 2026-10-28

Stars: 4
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Crux?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Crux need an API key?

No required environment variable is listed on this record.

What transport does Crux use?

Crux runs locally over stdio.

When was Crux last checked?

From the publisher

Documentation

What is CRUX?

One binary. One SQLite database. 12 layers of optimization.

Token costs drop — layered compression over tool descriptions, bash output, file reads, and conversation history.
Context stays lean — per-file read cache with delta replies and structural digests prevent re-reads.
Code is searchable — hybrid BM25 + dense vector + RRF search across code, memory, and conversation chunks.
Execution is safe — Linux rlimits, landlock, and optional seccomp; portable fallback on other platforms.
Output stays clean — comment slop guard strips AI-flavoured prose from source; humanizer rewrites raw AI output into concise text.
Zero telemetry — no cloud, no analytics, no network calls unless you opt in.

Quick start

# Install
cargo install crux

# Register CRUX inside every detected AI agent as an MCP server
crux setup

# Build with the comment-hygiene gate in front of cargo build
crux build --release

# Hybrid code search across the indexed project
crux search "delta cache" --kind code --limit 5

# Scan the workspace for AI-flavoured comments
crux hygiene comments --check

# Rewrite raw AI prose into concise text
crux humanize --mode concise --input "In conclusion, we leverage the robust pipeline."
# → We use the pipeline.

Or build from source: git clone https://github.com/Keradd/crux.git && cd crux && cargo build --release

Why CRUX?

Problem	CRUX solution
Agent re-reads the same files every turn	Layer 4 — read cache with mtime tracking, delta replies, structural digests
Tool descriptions eat context budget	Layer 2 — description shrinker strips redundant prose from MCP tool surfaces
Bash output is verbose and repetitive	Layer 3 — TOML-defined filters (3-tier: static, dynamic, structured)
Code search is slow or cloud-dependent	Layer 6 — hybrid BM25 (porter + trigram) + dense vectors + RRF, all local
Syntax trees are expensive to recompute	Layer 5 — persistent tree-sitter AST graph with cross-file call resolution
AI agents write overly verbose comments	Layer 12 — deterministic scanner, fixer, and stripper for AI-flavoured comments
Raw AI prose wastes tokens	Humanizer — deterministic local rewrite of verbose output into concise text
Unsafe code execution blows up context	Layer 7 — sandboxed subprocess with rlimits, landlock, seccomp

Features

Token optimization — layered compression across all 12 layers.
Context hygiene — read cache, delta replies, structural digests.
Hybrid search — BM25 porter + trigram + dense vectors + RRF.
AST graph — tree-sitter for 6 languages with cross-file call resolution.
Sandboxed execution — Linux rlimits + landlock + seccomp; cross-platform fallback.
Persistent memory — FTS5 + decay-ranked observations with contradiction detection.
Comment slop guard — detect, fix, and strip AI-flavoured source comments.
Output humanizer — rewrite raw AI prose into concise, natural text.
MCP tooling — stdio JSON-RPC server exposing 13 tools, plus description shrinker proxy.
Hygiene-aware build — crux build gates on comment hygiene before cargo build.

Commands

Command	Description
`crux setup`	Register CRUX inside every detected AI agent
`crux init`	Scaffold `.crux/`, `CLAUDE.md`, and project profile
`crux index` / `crux reindex`	Build AST graph and chunk store
`crux search <query>`	Hybrid BM25 + dense + RRF search
`crux find <name>` / `crux impact <symbol>`	Symbol lookup and blast radius
`crux execute --runtime <python\|bash\|node>`	Sandboxed code execution
`crux remember` / `crux recall`	Decay-ranked observation store
`crux bash <cmd>`	Run command through the filter pipeline
`crux hygiene comments --check\|--fix\|--strip`	AI-comment slop guard
`crux humanize --mode <mode>`	Rewrite AI-flavoured prose
`crux build`	Hygiene check + `cargo build`
`crux audit` / `crux stats`	Health snapshot and telemetry
`crux digest` / `crux compact`	Conversation turn-event rollups
`crux mcp` / `crux mcp-shrink`	MCP server or description shrinker proxy

CRUX_HOME overrides ~/.crux. CRUX_PROJECT overrides project-root detection.

Architecture

CRUX is a layered pipeline. Each layer compresses or transforms agent interactions independently:

Input → L1 (Output rules) → L2 (MCP shrink) → L3 (Bash filter) → L4 (Read cache)
         → L5 (AST graph) → L6 (Search) → L7 (Sandbox) → L8 (Memory)
         → L9 (Coach) → L10 (Setup) → L11 (Digest) → L12 (Hygiene)

See docs/ARCHITECTURE.md for the full design.

Documentation

Architecture — goals, tech stack, data model, per-layer internals, security model.
Install — from-source build, --features matrix, per-agent activation.
MCP tools — stdio server, description shrinker, full tool surface.
Humanizer — modes, examples, what it never touches.
Comment Hygiene — scanner, fixer, stripper behaviour.
Contributing — workspace conventions, PR checklist, comment rules.
Changelog — release history.
Examples — scaffolded projects to explore.

Privacy

Secrets handling: docs/ARCHITECTURE.md §14.2.

Development

MSRV: Rust 1.96. CI runs 5 jobs on Ubuntu + stable:

cargo fmt --all -- --check
cargo clippy --workspace --all-targets -- -D warnings
cargo test --workspace --exclude crux-l7-sandbox
RUSTDOCFLAGS="-D warnings" cargo doc --workspace --no-deps

Prefer crux build over cargo build — the hygiene gate runs first. See CONTRIBUTING.md for the full PR checklist.

License

Licensed under MIT OR Apache-2.0 at your option:

Contributions are dual-licensed under the same terms.