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PopNx MCPMCP servers for people who use AI · explained in plain words

Just MCP Server

by PromptExecutionversion 0.1.5i★ –iRuns on your computer
Registry nameio.github.PromptExecution/just-mcp

Install

Overview

Description from the maker (original English)

Expose curated Justfile recipes via MCP for safe deterministic automation.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "just": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/promptexecution/just-mcp:0.1.5"
      ]
    }
  }
}

Run this in your terminal

claude mcp add just -- docker run -i --rm ghcr.io/promptexecution/just-mcp:0.1.5

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "just": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/promptexecution/just-mcp:0.1.5"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "just": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/promptexecution/just-mcp:0.1.5"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account PromptExecution, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32655 servers in this category
  • Published to the registry more recently than 1% of the other 32655 servers in this category
  • Basic checks equal to or better than 100% of the other 32655 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Just MCP Server safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.5) reached the registry 12 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, SuperCollider

Alternatives

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
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Runs on your computerUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

just-mcp

👋 A way to let LLMs speak Just

A production-ready MCP server that provides seamless integration with Just command runner, enabling AI assistants to discover, execute, and introspect Justfile recipes through the standardized MCP protocol.

🎯 Why Just + MCP = Better Agent Execution

Context-Saving Abstraction

If it isn't immediately obvious, the benefit of having LLMs use Just vs. bash is that running Just commands (via MCP) provides a context-saving abstraction where they don't need to waste context opening/reading bash files, Python scripts, or other build artifacts. The LLM via MCP simply gets the command, parameters, and hints - it's in their memory as "these are commands available to you."

Eliminates the Justfile Learning Curve

No more watching LLMs execute just -l to get command lists, inevitably start reading the justfile, then try to write justfile syntax (like it's a Makefile), corrupt the justfile, and create a bad experience. Just's evolving syntax simply doesn't have a large enough corpus in frontier models today - we need more popular repos with justfiles in the training dataset.

Safer Than Raw Bash Access

Just-mcp is fundamentally safer than bash. If you read HackerNews, there's a story at least once daily about operators whose LLMs start forgetting, hallucinating, and eventually breaking down - deleting files and doing nasty unwanted things. Giving LLMs unsupervised, unrestricted bash access without carefully monitoring context consumption is a recipe for disaster.

Using Justfile fixes that. Even if the LLM modifies its own justfile, the next context is memoized by the justfile (hopefully in an idempotent git repo). This abstraction shields the llm from the command line complexity where hallucinations or attention tracking the current working directory cause it to go over the rails and off the cliff.

Powerful Agent Execution Tool

Just-mcp is perfect for anybody doing agent execution:

  • Ultra-low overhead - probably better than every other tool
  • Human-friendly - justfiles are easy for humans and low overhead for LLMs
  • Quick and dirty - while some prefer full Python FastAPI servers, just-mcp is just easy-as
  • sm0l model friendly - works great with self-hostable GPU/CPU open source models with 8k-32k context limits
Built-in Safety Patterns

Just has useful patterns for introducing:

  • Transparent logging without distracting the agent
  • Secondary model inspection - use sm0l models to scan commands asking "is this harmful?" before execution
  • Python decorator-like patterns for command validation
  • Idempotent execution backed by git repos

b00t

b00t mcp create just-mcp -- bash just-mcp --stdio "${REPO_ROOT}"

b00t mcp export just-mcp

🚀 Current Status: 67% Complete (8/12 core tasks)

✅ Implemented Features
  • 🏗️ Complete MCP Server - Full rmcp 0.3.0 integration with MCP 2024-11-05 protocol
  • 📋 Recipe Discovery - Parse and list all available Justfile recipes
  • ⚡ Recipe Execution - Execute recipes with parameters and capture structured output
  • 🔍 Recipe Introspection - Get detailed recipe information, parameters, and documentation
  • ✅ Justfile Validation - Syntax and semantic validation with error reporting
  • 🌍 Environment Management - Comprehensive .env file support and variable expansion
  • 🧪 Full Test Coverage - 33 passing tests across integration and unit test suites
🎯 MCP Tools Available
  1. `list_recipes` - List all available recipes in the justfile
  2. `run_recipe` - Execute a specific recipe with optional arguments
  3. `get_recipe_info` - Get detailed information about a specific recipe
  4. `validate_justfile` - Validate the justfile for syntax and semantic errors

🏃 Quick Start

Installation

Choose your preferred installation method:

npm (JavaScript/TypeScript)
# Install globally

npm install -g just-mcp

Or use with npx (no installation required)

npx just-mcp --stdio

pip (Python)
# Install with pip

pip install just-mcp

Or use with uvx (recommended)

uvx just-mcp --stdio

Cargo (Rust)
# Install from crates.io

cargo install just-mcp

Or build from source

git clone https://github.com/promptexecution/just-mcp cd just-mcp cargo build --release

pkgx (pkgxdev)
pkgx just-mcp --stdio

pkgx downloads the platform-specific tarball that GitHub releases expose (just-mcp-*-*.tar.gz), extracts the executable into ${PKGX_DIR:-$HOME/.pkgx}/bin, and runs the CLI with the arguments you pass. Add that bin directory to your shell’s PATH if you need just-mcp available long-term. The packaging manifest lives in pkgx/projects/github.com/promptexecution/just-mcp/package.yml and mirrors the pkgxdev/pantry entry.

Using Docker
# Pull the latest image from GitHub Container Registry

docker pull ghcr.io/promptexecution/just-mcp:latest

Run with Docker

docker run --rm -v $(pwd):/workspace ghcr.io/promptexecution/just-mcp:latest --stdio

Build locally

docker build -t just-mcp:local . docker run --rm -v $(pwd):/workspace just-mcp:local --stdio

Available Docker image tags:

  • latest - Latest stable release
  • X.Y.Z - Specific version (e.g., 0.1.0)
  • X.Y - Latest patch version (e.g., 0.1)
  • X - Latest minor version (e.g., 0)
Claude Desktop Integration
Using npm/npx

Add to your Claude Desktop MCP configuration:

Using Binary
{

"mcpServers": { "just-mcp": { "command": "npx", "args": ["-y", "just-mcp", "--stdio"] } } }

Using pip/uvx
{

"mcpServers": { "just-mcp": { "command": "uvx", "args": ["just-mcp", "--stdio"] } } }

Using cargo or manual install
{

"mcpServers": { "just-mcp": { "command": "/path/to/just-mcp", "args": ["--stdio"] } } }

Using Docker
{

"mcpServers": { "just-mcp": { "command": "docker", "args": [ "run", "--rm", "-i", "-v", "${workspaceFolder}:/workspace", "ghcr.io/promptexecution/just-mcp:latest", "--stdio" ] } } }

Usage Examples
# Run as MCP server

just-mcp --stdio

Run in specific directory

just-mcp --directory /path/to/project --stdio

Using Docker

docker run --rm -v $(pwd):/workspace ghcr.io/promptexecution/just-mcp:latest --stdio

🧪 Testing

Comprehensive Test Suite
# Run all tests (33 tests)

cargo test

Run specific test suites

cargo test --test basic_mcp_test # Protocol compliance testing cargo test --test mcp_integration_working # SDK integration testing

Test Architecture
  • `basic_mcp_test.rs` - Direct protocol compliance testing using raw JSON-RPC
  • `mcp_integration_working.rs` - Type-safe SDK integration testing with rmcp client
  • Unit tests - 25+ tests covering parser, executor, validator, and environment modules

📚 Architecture

Project Structure
just-mcp/

├── src/main.rs # CLI binary ├── just-mcp-lib/ # Core library │ ├── parser.rs # Justfile parsing │ ├── executor.rs # Recipe execution │ ├── validator.rs # Validation logic │ ├── environment.rs # Environment management │ └── mcp_server.rs # MCP protocol implementation ├── tests/ # Integration tests └── justfile # Demo recipes

Tech Stack
  • Rust 1.82+ with async/await support
  • rmcp 0.3.0 - Official MCP SDK for Rust
  • serde/serde_json - JSON serialization
  • snafu - Structured error handling
  • tokio - Async runtime

🔄 Development Roadmap

🎯 Next Priority Tasks (Remaining 33%)
  1. LSP-Style Completion System - Intelligent autocompletion for recipes and parameters
  2. Enhanced Diagnostics - Advanced syntax error reporting and suggestions
  3. Virtual File System - Support for stdin, remote sources, and in-memory buffers
  4. Release Preparation - Documentation, CI/CD, and crate publication
🚀 Future Enhancements
  • Plugin system for custom recipe types
  • Integration with other build tools
  • Performance optimizations for large justfiles
  • Advanced dependency visualization

📖 Usage Patterns

Recipe Execution
// List available recipes

await client.callTool("list_recipes", {});

// Execute recipe with parameters await client.callTool("run_recipe", { "recipe_name": "build", "args": "[\"--release\"]" });

// Get recipe information await client.callTool("get_recipe_info", { "recipe_name": "test" });

Validation
// Validate justfile

await client.callTool("validate_justfile", { "justfile_path": "./custom.justfile" });

🤝 Contributing

This project follows the _b00t_ development methodology:

  • TDD Approach - Tests first, implementation second
  • Feature Branches - Never work directly on main branch
  • Structured Errors - Use snafu for error management
  • Git Workflow - Clean commits with descriptive messages
Development Commands
just build    # Build the project

just test # Run tests just server # Start MCP server just clean # Clean build artifacts

📄 License

This project is licensed under LICENSE.

🚀 Release Setup & CI/CD

✅ Completed Setup
Cocogitto & Conventional Commits
  • Installed cocogitto for conventional commit enforcement
  • Configured cog.toml with proper commit types and changelog settings
  • Set up git hooks for commit message linting (commit-msg) and pre-push testing
GitHub Actions CI/CD
  • CI Pipeline (ci.yml): Multi-platform testing (Ubuntu, Windows, macOS), formatting, clippy, commit linting
  • Release Pipeline (release.yml): Automated versioning, changelog generation, GitHub releases, and crates.io publishing
  • Binary Builds (build-binaries.yml): Cross-platform binary compilation for npm and pip packages
  • Container Pipeline (container.yaml): Multi-platform Docker image builds (linux/amd64, linux/arm64) pushed to GitHub Container Registry
Docker Images
  • Multi-platform builds for linux/amd64 and linux/arm64
  • Minimal image size using static musl binaries and scratch base image
  • Automatic tagging with semantic versioning (major, major.minor, major.minor.patch, latest)
  • Published to GitHub Container Registry (ghcr.io)
  • Integrated with release workflow for automatic deployment
Crates.io Preparation
  • Updated both Cargo.toml files with complete metadata (description, keywords, categories, license, etc.)
  • Added proper exclusions for development-only files
  • Verified MIT license is in place
Documentation & Structure
  • README.md is production-ready with installation and usage instructions
  • Created initial CHANGELOG.md for release tracking
  • Updated .gitignore with Rust-specific entries
🚀 Production Deployment
Development Workflow:
  • All commits must follow convention

Only the beginning is shown; read the rest in the repo

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