Crush

Crush

Charm
FastMCP

FastMCP

fastmcp
+
+

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About

Crush is a glamorous AI coding agent that lives right in your terminal, seamlessly connecting your tools, code, and workflows with any Large Language Model (LLM) of your choice. It offers multi-model flexibility, letting you choose from a variety of LLMs or add your own using OpenAI or Anthropic-compatible APIs, and supports mid-session switching between them while preserving context. Crush is session-based, enabling multiple project-specific contexts to coexist. Powered by Language Server Protocol (LSP) enhancements, it incorporates coding-aware context just like a developer’s editor. It's highly extensible via Model Context Protocol (MCP) plugins using HTTP, stdio, or SSE for added capabilities. Crush runs anywhere, leveraging Charm’s sleek Bubble Tea-based TUI for a polished terminal user experience. Written in Go and MIT-licensed (with FSL-1.1 for trademarks), enabling developers to stay in their terminal while taking advantage of expressive AI coding assistance.

About

FastMCP is an open source, Pythonic framework for building Model Context Protocol (MCP) applications that makes creating, managing, and interacting with MCP servers simple and production-ready by handling the protocol’s complexity so developers can focus on business logic. The Model Context Protocol (MCP) is a standardized way for large language models to securely connect to tools, data, and services, and FastMCP provides a clean API to implement that protocol with minimal boilerplate, using Python decorators to register tools, resources, and prompts. A typical FastMCP server is created by instantiating a FastMCP object, decorating Python functions as tools (functions the LLM can invoke), and then running the server with built-in transport options like stdio or HTTP; this lets AI clients call into your code as if it were part of the model’s context.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers and technical users in search of a solution offering an AI-powered coding assistant that integrates seamlessly with their workflows

Audience

Python developers and AI engineers who want a high-level, production-ready framework to build and deploy MCP servers that expose tools and data to LLMs securely and efficiently

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Pros & Cons from Real Users

Pros

  • 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.

Cons

  • 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.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Charm
Founded: 2019
United States
github.com/charmbracelet/crush

Company Information

fastmcp
Founded: 2025
United States
gofastmcp.com/getting-started/welcome

Alternatives

Factory Droid

Factory Droid

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Alternatives

OpenCode

OpenCode

Anomaly Innovations
Auggie CLI

Auggie CLI

Augment Code
Cline

Cline

Cline AI Coding Agent

Categories

Categories

Integrations

Model Context Protocol (MCP)
Amazon Bedrock
Claude
Claude Max
FreeBSD
GLM Coding Plan
Gemini Enterprise Agent Platform
GitHub Copilot
Go
JSON
LM Studio
Markdown
NetBSD
OAuth
Ollama
OpenAI
OpenBSD
OpenSpec
PowerShell
Python

Integrations

Model Context Protocol (MCP)
Amazon Bedrock
Claude
Claude Max
FreeBSD
GLM Coding Plan
Gemini Enterprise Agent Platform
GitHub Copilot
Go
JSON
LM Studio
Markdown
NetBSD
OAuth
Ollama
OpenAI
OpenBSD
OpenSpec
PowerShell
Python
Claim Crush and update features and information
Claim Crush and update features and information
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