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Personal AI coding agent with memory, tool execution, and safety controls

Project description

  __  __               _
 |  \/  | ___ ___   __| | ___
 | |\/| |/ __/ _ \ / _` |/ _ \
 | |  | | (_| (_) | (_| |  __/
 |_|  |_|\___\___/ \__,_|\___|
 ──────────────────────────────────────────────────────────────────────
  Mcode  —  Your local AI coding agent
  › /help for commands
  › Project: default  —  /project rename <name> to name this session
  › Model:   minimax  (MiniMax-M2.7)  —  /model to switch
 ──────────────────────────────────────────────────────────────────────

PyPI Python License Language

Personal AI coding agent CLI — memory, tools, and safety controls.

Installation

pip install memocode && mcode

Features

Agentic loop Native function calling, stuck detection, fully autonomous auto mode
Memory 4-layer cross-session memory with compression, recall, and Ebbinghaus forgetting
Projects Multiple projects, each with isolated memory DB and working directory
Image support Attach images via @path for multimodal turns with vision-capable models
Safety Human / Auto / Bypass modes with zone checks, whitelists, and file backups
Extensible Drop .py files into ~/.mcode/tools/ to add custom tools

Installation

pip install memocode

On first run, ~/.mcode/agent.json is created. Configure your model:

{
  "active_model": "minimax",
  "models": {
    "minimax": {
      "provider": "openai",
      "model": "MiniMax-M2.7",
      "base_url": "https://api.minimaxi.com/v1",
      "api_key_env": "MINIMAX_API_KEY",
      "context_window": 65536,
      "extra_body": {"reasoning_split": true}
    }
  }
}
export MINIMAX_API_KEY=your_key_here
mcode

Any OpenAI-compatible endpoint works. Multiple models can be defined and switched with /model.


Usage

mcode                      # Start (auto-resumes last project)
mcode --project myapp      # Start with a specific project
mcode --verbose            # Show full tracebacks on errors

Slash Commands

Session

Command Description
/help Show all commands
/status Show current settings
/end End session and save to memory
/quit / /exit Exit

Conversation

Command Description
/btw <question> Quick one-shot question — no memory, no tools
/undo Undo last run — restore files and/or rewind conversation
/rewind [N] Rewind conversation to turn N
/rollback Restore a specific backed-up file
/history [N] Show audit log

Auto mode

Command Description
/auto [on|off] Toggle autonomous mode
/auto whitelist [list|add|remove|reset] Manage whitelisted shell commands
/template [example] Show recommended task prompt template

Safety

Command Description
/safety [on|off] Toggle safety bypass (DANGEROUS, session-only)

Projects

Command Description
/project list List all projects
/project workdir [path] Set working directory
/project rename [<old>] <new> Rename a project
/project delete <name> Delete a project (glob patterns supported)

Memory

Command Description
/memory Show core memory (user profile)
/memory set <key> <value> Write an entry
/memory del <key> Delete an entry
/memory pin <key> Pin an entry (never forgets)

Other

Command Description
/model [name] Show or switch LLM model
/tools List all loaded tools
!<command> Run a shell command directly (safety-checked)
@<path> Attach a file — text files are inlined, images sent as multimodal content

Memory System

mcode maintains four memory layers across sessions:

Layer Scope Contents
Core memory Global User traits: communication style, autonomy preference
Project memory Per-project Decisions, architecture, conventions, progress
Recent memory Per-project Compressed summaries of past sessions
Session history Per-project Current session verbatim; older turns compressed in-place

Recall

  • Recent summaries are injected every turn (newest-first, 4k token cap) with timestamps so the model can answer timeline questions
  • memory_search is called automatically when context is missing — searches the full summary history
  • Core and project memory are always in the system prefix (prompt-cache eligible)

Compression When context reaches 50% of context_window, old turns are replaced with a structured summary: topics, decisions, progress, pending items. Raw code is excluded — only decisions and rationale are preserved.

Forgetting Core memory decays via the Ebbinghaus curve (score = exp(-t / stability)). Each judge reinforcement grows the entry's stability by 10% (capped at 2× the dimension default), so frequently confirmed traits resist forgetting longer. Entries never reinforced gradually fade below the 0.1 threshold and are dropped.


Auto Mode

Auto mode runs the agent fully autonomously — no prompts, hard boundaries (whitelist-only shell commands, writes restricted to work_dir).

Enable with /auto on, then use /template for the recommended task structure:

Task: <one-line goal>
Context: work_dir, language/framework, entry point
Acceptance criteria: 1) ... 2) ... 3) ...
Constraints: do NOT modify <files>
Verify by running: <test command>

Safety Modes

Mode Behavior
Human (default) Prompts before risky ops; backs up files before destructive edits
Auto (/auto on) No prompts; blocks non-whitelisted commands and out-of-work_dir writes
Bypass (/safety off) Skips all checks; session-only; requires typing yes to confirm

Built-in Tools

Tool Description
shell_exec Run shell commands with streaming output
file_read Read file with optional pagination
file_write Write or append to a file
file_edit Targeted string replacement
glob Find files by pattern (**/*.py)
grep Search file content by regex
web_fetch Fetch a URL, returns readable text (HTML stripped)
memory_search Search past session summaries for relevant context

Custom Tools

Drop a .py file in ~/.mcode/tools/:

from tools.registry import Tool, ToolSchema

def _my_tool(param: str) -> str:
    return f"result: {param}"

MY_TOOL = Tool(
    schema=ToolSchema(
        name="my_tool",
        description="Description shown to the model",
        parameters={
            "type": "object",
            "properties": {"param": {"type": "string"}},
            "required": ["param"],
        },
    ),
    fn=_my_tool,
)

Project Structure

mcode/
├── run.py                       # CLI entry point
├── control/
│   ├── brain.py                 # Agent loop, tool dispatch, safety
│   ├── llm.py                   # LLM adapter (OpenAI-compatible)
│   ├── project_manager.py       # Project registry
│   ├── audit.py                 # Audit log
│   └── chatmem/                 # Memory system
│       ├── context_manager.py   # History, compression, injection
│       ├── compressor.py        # LLM-based summarization
│       └── memory/
│           ├── core_memory.py   # User traits (global, with forgetting)
│           ├── recent_memory.py # Cross-session summaries (per-project)
│           ├── consolidation.py # Pattern extraction → core memory
│           └── forgetting.py    # Ebbinghaus decay
├── tools/
│   ├── file.py                  # file_read/write/edit, glob, grep
│   ├── shell.py                 # shell_exec
│   ├── web.py                   # web_fetch
│   └── registry.py              # Tool registry + loader
└── safety/
    ├── safety.py                # Zone checks, auto mode rules
    ├── backup.py                # File backup
    └── policy.py                # Persistent always-allow policies

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