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Developer-Tools

Crush

ai-coding developer-tools command-line terminal multi-model charmbracelet

Crush represents Charmbracelet’s entry into the AI coding assistant space, bringing their signature terminal-first philosophy and “glamourous” design aesthetic to AI-powered development. Built as a native terminal application, Crush distinguishes itself through its exceptional multi-model support, flexible configuration options, and deep integration with developer workflows through LSP and MCP protocols.

Core Features

Terminal-First Design

  • Native CLI Experience: Fully optimized for terminal workflows with keyboard-driven interaction
  • Cross-Platform Support: First-class support on macOS, Linux, Windows (PowerShell and WSL), FreeBSD, OpenBSD, and NetBSD
  • Minimal Resource Footprint: Lightweight Go-based implementation with fast startup and response times
  • Session Management: Multiple work sessions with context preservation per project

Multi-Model Architecture

  • Provider Flexibility: Choose from Anthropic, OpenAI, Groq, OpenRouter, Google Gemini, Cerebras, HuggingFace, VertexAI, Amazon Bedrock, and more
  • Custom Provider Support: Add your own OpenAI-compatible or Anthropic-compatible APIs
  • Model Switching: Switch LLMs mid-session while preserving context and conversation history
  • Cost Tracking: Built-in cost tracking and token usage monitoring

Enhanced Context Awareness

  • LSP Integration: Uses Language Server Protocol for additional context, just like modern IDEs
  • MCP Support: Extensible via Model Context Protocol (stdio, http, and sse transport types)
  • Project Initialization: Analyzes codebase and creates context files for future sessions
  • Git Integration: Native support for version control workflows with attribution options

Technical Specifications

  • Language: Go (98%) with minimal Smarty templating
  • Installation: Homebrew, NPM, Winget, Scoop, Arch Linux, Nix, Debian/Ubuntu, Fedora/RHEL, or direct binary download
  • Configuration: JSON-based with project-local and global options
  • License: FSL-1.1-MIT (Fair Source License)
  • Repository: 15.4k+ stars, 883+ forks on GitHub
  • Release Cadence: Regular updates with 75+ releases

Installation Methods

Package Managers

bash
# Homebrew
brew install charmbracelet/tap/crush

# NPM
npm install -g @charmland/crush

# Winget (Windows)
winget install charmbracelet.crush

# Scoop (Windows)
scoop install crush

# Arch Linux
yay -S crush-bin

# Nix
nix run github:numtide/nix-ai-tools#crush

System Package Installation

bash
# Debian/Ubuntu
sudo mkdir -p /etc/apt/keyrings
curl -fsSL https://repo.charm.sh/apt/gpg.key | sudo gpg --dearmor -o /etc/apt/keyrings/charm.gpg
echo "deb [signed-by=/etc/apt/keyrings/charm.gpg] https://repo.charm.sh/apt/ * *" | sudo tee /etc/apt/sources.list.d/charm.list
sudo apt update && sudo apt install crush

# Fedora/RHEL
echo '[charm]
name=Charm
baseurl=https://repo.charm.sh/yum/
enabled=1
gpgcheck=1
gpgkey=https://repo.charm.sh/yum/gpg.key' | sudo tee /etc/yum.repos.d/charm.repo
sudo yum install crush

Direct Installation

bash
# Go install
go install github.com/charmbracelet/crush@latest

Configuration

Quick Setup

Crush runs great with no configuration. Simply set an API key for your preferred provider:

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GitHits

code-search ai-assistance code-examples open-source developer-tools

GitHits is an AI-powered code search platform that provides short, focused, verified code examples from global open source repositories. It helps developers solve specific problems by delivering canonical code solutions rather than overwhelming them with options.

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Context7

documentation library-research ai-assistance context-gathering developer-tools

Context7 is a specialized AI platform designed to provide coding agents and developers with rapid access to current library documentation and API references. It acts as a librarian subagent, intelligently searching through repositories and documentation sites to gather relevant context before development work begins.

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Grokipedia

ai-coding knowledge-management developer-tools real-time-ai fact-checking

Grokipedia represents a revolutionary leap forward in knowledge managementβ€”combining the power of AI with human judgment to create a dynamic, self-correcting encyclopedia that evolves in real-time. Launched in October 2025, Grokipedia isn’t just an updated Wikipedia; it’s a fundamentally new approach to building and maintaining the world’s most accurate source of truth.

Core Features

Real-time AI Reconsideration

  • Dynamic Content Updates: Grok reconsiders and updates information instantly based on user feedback
  • Transparent Correction Process: Shows what was wrong, why it was wrong, and what got fixed
  • Continuous Learning: AI improves with each human interaction and correction
  • Version History: Complete traceability of all changes and improvements

Interactive Fact-Checking System

  • Line-by-Line Highlighting: Users can flag any specific content for review
  • Contextual Feedback: Add detailed context and reasoning for corrections
  • Real-time Collaboration: Watch as AI processes and incorporates human insights
  • Multi-Perspective Analysis: Considers multiple viewpoints before making corrections

Human-AI Knowledge Partnership

  • Human Judgment: Provides nuance, context, and ethical considerations
  • AI Processing: Delivers speed, scale, and pattern recognition capabilities
  • Collaborative Intelligence: Combines strengths of both human and artificial intelligence
  • Quality Assurance: Multi-layered review process ensures accuracy

Technical Specifications

  • Platforms: Web-based platform with mobile optimization
  • API Access: RESTful API for integration with development tools and applications
  • Real-time Processing: Sub-second response times for content reconsideration
  • Version Control: Complete edit history with change tracking and attribution
  • Privacy: User data protection with transparent content policies
  • Scalability: Cloud-native architecture supporting global user base

Unique Advantages

Transparent Knowledge Evolution

Unlike traditional encyclopedias that present information as static facts, Grokipedia shows the journey of knowledgeβ€”how discoveries are made, corrections are implemented, and understanding evolves over time. This transparency creates a learning environment where users understand not just what to think, but how knowledge itself develops.

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