Crush Description

Crush is a sophisticated AI coding assistant that resides directly in your terminal, effortlessly linking your tools, code, and workflows with any large language model (LLM) you prefer. It features versatility in model selection, allowing you to pick from a range of LLMs or integrate your own through OpenAI or Anthropic-compatible APIs, and it facilitates mid-session transitions between these models while maintaining contextual integrity. Designed for session-based functionality, Crush supports multiple project-specific contexts operating simultaneously. Enhanced by Language Server Protocol (LSP) improvements, it offers coding-aware context similar to what developers find in their preferred editors. This tool is highly customizable, utilizing Model Context Protocol (MCP) plugins via HTTP, stdio, or SSE to expand its capabilities. Crush can be executed on any platform, utilizing Charm’s elegant Bubble Tea-based TUI to provide a refined terminal user experience. Developed in Go and distributed under the MIT license (with FSL-1.1 for trademark considerations), Crush empowers developers to remain in their terminal while benefiting from advanced AI coding support, thereby streamlining their workflow like never before. Its innovative design not only enhances productivity but also encourages a seamless integration of AI into everyday coding practices.

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Pricing

Pricing Starts At:
Free
Free Version:
Yes

Integrations

API:
Yes, Crush has an API
View Integrations

Reviews - 1 Verified Review

Total
ease
features
design
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Company Details

Company:
Charm
Year Founded:
2019
Headquarters:
United States
Website:
github.com/charmbracelet/crush

Media

Play Video Crush Screenshot 1 Crush Screenshot 2
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Product Details

Platforms
Windows
Mac
Linux
Types of Training
Training Docs
In Person
Training Videos
Customer Support
Business Hours
Online Support

Crush Features and Options

Crush User Reviews

Write a Review
  • Name: Anonymous (Verified)
    Job Title: Developer
    Length of product use: Less than 6 months
    Used How Often?: Daily
    Role: User
    Organization Size: 5,000 - 9,999
    Features
    Design
    Ease
    Likelihood to Recommend to Others
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    Crush AI coding agent review

    Date: Jul 31 2026

    Summary: Five stars from me. Crush feels like a strong AI coding agent for developers who want something terminal-native, open source, customizable, and close to their real workflow.

    It is not a magic autopilot, and I would not run it recklessly. But as a supervised coding partner for debugging, refactoring, repo exploration, command-line workflows, and agentic development, Crush looks like one of the more interesting tools in the AI coding agent space.

    Positive: Crush is really appealing from a developer’s point of view because it brings agentic coding into the terminal without making the workflow feel bloated. It feels like a tool for people who already live in the command line and want an AI agent that can work with their existing code, tools, and habits.

    I like that it is open source and model-flexible. Being able to wire your own LLM into the workflow is a big deal because different coding tasks need different tradeoffs around cost, speed, context, and reasoning quality.

    The terminal UI is also a nice fit for real development work. Crush is not trying to replace the whole IDE; it gives you an agentic layer where you can ask for help, work through code, run commands, and stay close to the environment you already use.

    The active GitHub repo is a good sign too. Frequent commits, lots of stars, and ongoing work around providers, MCP, hooks, and shell features make it feel like a project with real momentum instead of a one-off AI demo.

    Negative: Crush is probably not the best fit for someone who wants a polished, hand-holdy coding assistant with everything abstracted away. It feels more geared toward developers who are comfortable in the terminal and want control over models, config, permissions, and workflows.

    I would also be careful with any AI coding agent that can interact with your shell and project files. Recent research on coding-agent setup workflows shows that agents can be vulnerable to malicious or misleading project instructions, dependency names, registry redirects, and unsafe install steps, so developers still need review habits and guardrails.

    For production repos, I would keep permissions tight, review commands, watch file diffs, and avoid letting any agent run destructive operations without explicit approval.

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