microcode 0.2.0

Minimal Terminal Agent powered by RLMs

Microcode

Minimal Terminal Agent powered by RLMs

Microcode is an efficient terminal-based AI agent with an internal REPL environment for coding assistance. It leverages Reasoning Language Models (RLMs) to help developers with coding tasks directly from the command line. Because we are solely using RLMs, it can handle extra large code snippets, file contents, and pasted content without dumping it directly into the context window. Try running with the --verbose flag to view the trajectories, or the "internal monologue" of the agent.

Warning: Microcode is currently in beta and does not yet have the standard guardrails (suching as asking the user to accept changes) as production coding agents. Use at your own risk.

Features

• Verbose Output - Enable verbose output for debugging
• Interactive CLI - Seamless conversational interface with AI models
• Multiple Model Support - Choose from various AI providers (OpenAI, Anthropic, Google, Qwen, etc.)
• MCP Integration - Model Context Protocol server support for extended capabilities
• Smart Caching - Persistent settings, API keys, and model configurations
• Rich Terminal UI - Beautiful output with markdown rendering, gradient banners, and status indicators
• Paste Support - Handle large code snippets and file contents with ease
• Configurable - Environment variables and CLI flags for full customization

Installation

Prerequisites

• Python 3.11 or higher
• uv (recommended) or pip
• Deno (RLM runtime for the REPL)

Install Deno with one of the following:

curl -fsSL https://deno.land/install.sh | sh

brew install deno

Install via uv (recommended)

uv tool install microcode

Upgrade via uv

uv tool upgrade microcode

Install via pip

pip install microcode

Install from source

git clone https://github.com/modaic-ai/microcode.git
cd microcode
uv sync  # or: pip install -e .

Configuration

API Key Setup

Microcode uses OpenRouter for model access. Set your API key using one of these methods:

1. Environment Variable (recommended for CI/CD):

   export OPENROUTER_API_KEY="your-api-key"
   

2. Interactive Setup (persisted to cache):

   microcode
   /key  # Then enter your API key when prompted
   

Environment Variables

Variable	Description	Default
OPENROUTER_API_KEY	OpenRouter API key	-
MICROCODE_MODEL	Primary model ID	Auto-selected
MICROCODE_SUB_LM	Sub-model for auxiliary tasks	Auto-selected
MICROCODE_MAX_ITERATIONS	Max iterations per task	-
MICROCODE_MAX_TOKENS	Max tokens per response	-
MICROCODE_MAX_OUTPUT_CHARS	Max output characters	-
MICROCODE_API_BASE	Custom API base URL	-
MICROCODE_VERBOSE	Enable verbose logging (1/0)	0
MODAIC_ENV / MICROCODE_ENV	Environment (dev/prod)	prod

Usage

Starting the CLI

microcode

CLI Options

microcode --help

Flag	Description
--model, -m	Override primary model
--sub-lm, -s	Override sub-model
--api-key, -k	Provide API key directly
--max-iterations	Set max iterations
--max-tokens	Set max tokens
--max-output-chars	Set max output characters
--api-base	Custom API base URL
--verbose, -v	Enable verbose output
--env	Set environment (dev/prod)
--history-limit	Conversation history limit
--no-banner	Disable startup banner

Interactive Commands

Once in the CLI, use these commands:

Command	Description
/help, /h, ?	Show help menu
/q, exit	Exit the CLI
/clear, /cls	Clear the terminal screen
/c	Clear conversation history
/key [key]	Set OpenRouter API key (or enter interactively)
/key clear	Remove stored API key
/model	Change primary model via TUI selector
/model <id>	Set primary model directly
/mcp add <name> <command>	Add an MCP server

Available Models

#	Model	Provider
1	GPT-5.2 Codex	OpenAI
2	GPT-5.2	OpenAI
3	Claude Opus 4.5	Anthropic
4	Claude Opus 4	Anthropic
5	Qwen 3 Coder	Qwen
6	Gemini 3 Flash Preview	Google
7	Kimi K2 0905	Moonshot AI
8	Minimax M2.1	Minimax

Project Structure

microcode/
├── main.py              # Entry point and interactive CLI loop
├── pyproject.toml       # Project configuration and dependencies
├── utils/
│   ├── __init__.py
│   ├── cache.py         # API key and settings persistence
│   ├── constants.py     # Colors, models, paths, and banner art
│   ├── display.py       # Terminal rendering and UI utilities
│   ├── mcp.py           # MCP server integration
│   ├── models.py        # Model selection and configuration
│   └── paste.py         # Clipboard and paste handling
└── tests/
    └── test_main_settings.py

Key Components

• main.py - Orchestrates the interactive session, handles user input, manages conversation history, and invokes the AI agent via Modaic's AutoProgram
• utils/cache.py - Secure storage for API keys and user preferences using JSON files
• utils/constants.py - Centralized configuration including available models, ANSI color codes, and file paths
• utils/display.py - Terminal output formatting, markdown rendering, and the startup banner
• utils/models.py - Model selection TUI using Textual, model ID normalization, and agent reconfiguration
• utils/mcp.py - Model Context Protocol server registration and management
• utils/paste.py - Handles large text inputs via placeholder replacement

Development

Setting Up Development Environment

git clone https://github.com/modaic-ai/microcode.git
cd microcode
uv sync --dev

Running Tests

uv run pytest tests/

Code Style

The project follows standard Python conventions. Use type hints for all function signatures.

Dependencies

Core dependencies:

• click / typer - CLI framework
• modaic - RLM program execution
• dspy - Language model programming
• mcp2py - MCP integration
• rich - Rich terminal output
• textual - Terminal UI framework
• prompt-toolkit - Input handling

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Links

• Homepage: https://modaic.dev/
• Repository: https://github.com/modaic-ai/microcode
• Issues: https://github.com/modaic-ai/microcode/issues

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