memocode 0.4.30

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

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

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": 128000
    }
  }
}

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
/rewind [N]	Pick a turn to rewind to, then clear conversation and/or restore files; /rewind 0 clears everything
/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: interaction style, delegation 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)
• Project memory entries include an age marker (e.g. 14d ago) so the model can assess data freshness

Compression When context reaches 50% of context_window, old turns are replaced with a structured summary: topics, decisions, progress, pending items. Summaries use explicit markers (Rejected X — reason, Changed from X to Y — reason) so negations and reversals are directly retrievable. Compression mode is auto-detected per session: conversations without code use plan mode (preserves specific values, dates, URLs, identifiers); code-heavy conversations use code mode (focuses on decisions and rationale). Override via compression_mode in chatmem.json ("auto" / "code" / "plan").

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. Project memory is not subject to decay — decisions persist until explicitly overwritten or deleted.

---

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 — supports GET/POST/PUT/PATCH/DELETE, custom headers, JSON body
web_search	Search the web via DuckDuckGo — no API key required
pdf_read	Extract text from PDF files (requires pdfplumber or pypdf)
excel_read	Read Excel (.xlsx) or CSV files as formatted table (requires openpyxl)
excel_write	Write data to Excel (.xlsx) or CSV files (requires openpyxl)
calc	Safe arithmetic evaluator — any math expression, never computed mentally
memory_search	Search past session summaries for relevant context
activity_log_query	Query recent activity log — for "today / this session / past N days" questions
project_query	Read structured project memory — decisions, architecture, progress; prefer over memory_search for current-state questions

---

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
│   ├── calc.py                  # calc — safe arithmetic evaluator
│   └── registry.py              # Tool registry + loader
└── safety/
    ├── safety.py                # Zone checks, auto mode rules
    ├── backup.py                # File backup
    └── policy.py                # Persistent always-allow policies