Entries matching “desktop”

@EtienneLescot

@EtienneLescot

A desktop app for Muse Code on macOS and Windows with projects, git worktrees, subagents, MCP, a diff review panel and opt-in computer use that lets the agent see the screen and use apps.

@srikantmehra57

@srikantmehra57

An independent desktop command center for the Muse Code CLI that brings workspaces, sessions, approvals, reasoning controls, changed files and agent activity into one interface.

@emonibnmustafa

@emonibnmustafa

A local translation gateway and profile manager that plugs Meta Muse Spark (or DeepSeek, Groq, Ollama) into OpenAI Codex and ChatGPT Desktop, translating tool calls and SSE streams, with a one-command switch between providers.

After running out of quota on two Codex subscriptions, found it was almost trivially easy to run Muse Spark 1.3 in Codex Desktop; not as good as Astra, but cheap and it one-shots most of his prompts.

@kevintsai1202

@kevintsai1202

MCP server that gives Claude Code, Claude Desktop, Cursor and other MCP clients image generation and editing powered by Meta's Muse image model, published to npm.

@danny-hines

@danny-hines

Call Muse Code from Codex or ChatGPT desktop via MCP tools and skills for independent code review, approach comparison or delegated implementation, using a Muse Code subscription or API key.

@jason-snell

@jason-snell

windows-cua is a native C++ Win32 port of Meta's macOS computer-use agent that drives Muse Spark 1.1 through the Responses API to see and operate a real Windows desktop.

@aminamos

@aminamos

Four graphical frontends for Muse Code (Tauri apps for Windows and macOS, Expo apps for iOS and Android) plus a Deno relay, so every run executes through muse on the subscription login.

Julian Goldie's GoldieBench scores Muse Spark 1.2 at 7.55/10 across 50 one-shot builds. It did well on fractals (8.7), a macOS desktop sim (8.6) and a galaxy viz (8.6), but 3D games like Doom and Dragonrealm often came out incomplete or black.

harjot.co

@harjjotsinghh

I pay for @Muse Code but didn't want to live in a terminal. On Windows it's WSL-only. So I built Helicon: an open-source desktop app for the actual Muse CLI. • uses your existing muse login, no API key • talks to muse serve over MSP, so Muse stays the agent • resumes

@HarjjotSinghh

@HarjjotSinghh

Helicon is an open-source desktop and web app that wraps Meta's Muse Code CLI in a Codex/Claude-style interface, grouping sessions by project with history, resume and diffs on Windows, macOS and WSL2.

@raksix

@raksix

A documented setup that runs Muse Spark 1.3 Contributor inside Claude Desktop on macOS through a small Node proxy that translates Anthropic requests to OpenCode Go's OpenAI-style API.

Chetaslua

@chetaslua

I made 4 free models fight in one window 😱 same snake spec , 4 agents in parallel just Cline Desktop , the open source app for open weight models > GLM 5.3 Flash 152 pellets > Muse Spark 1.3 151 > DeepSeek V4 Flash 138 < patched a real bug in its own bot > > Solar Pro 4 0 ,

@atameric

@atameric

An unofficial macOS desktop client that speaks MSP over muse serve, offering streaming markdown, visible tool calls, session history shared with the terminal and screenshot attachments.

@Telep-IO

@Telep-IO

Omusey is an Omarchy plugin that puts Muse chat in the Linux desktop bar as a dropdown that can pop out into its own window.

@Fangyuan025

@Fangyuan025

Chaty is a private offline desktop app built on Rust and llama.cpp that runs Muse Glimmer and other open models locally with a coding agent, RAG knowledge base, deep research and voice.

Disclaimer. This is the first time I've used Muse or VSCode as a harness. The reason I am using VSCode as a harness is this is a research project for my job, and we only have VSCode, Codex, and Claude Code approved for harnesses. I ran it in a folder with only one HTML file (800 lines) that is a Roblox-style COD game. I just gave it a prompt "Can you fix the bugs in the file". It read the file 3 times, found one bug, started to fix it, then got stuck reading the same 10 lines over and over. I imagine it's one of these three issues. • It's a prompt error, being way too vague/open ended for the capabilities of a smaller model. I tried again, with a specific prompt to fix a specific bug, and it still just ends up so confused, trying to grep/find the file despite already having read it, and trying to find the code inside of the file. • It's a limitation of small models running with a large harness/having way too much going on. I tried running it with Pi with its default prompt, and it just got stuck doing tool calls and never actually read the file. Tried running this just directly in the Unsloth Desktop UI with no harness but it failed to parse the file I inputted and tried to gen

Wavect's guide covers Glimmer's hardware targets (24–32GB) and tool-use scores such as MCP-Atlas 75.5 and SWE-Bench Pro 51.2, and recommends a 20–30 task pilot before production.