memcord

What's new in v4.2.0 — Per-slot custom_storage_path now shares the slot's full settings (not just data) across devices via a local storage-links registry.

Table of Contents

• Core Benefits
• Prerequisites
• Quick Start
• Keeping Memcord Updated
• Using Memcord
• Custom Storage Path
• Summarizer Backends
• IDE Configuration
• Documentation

Core Benefits

• Infinite Memory - Claude remembers everything across unlimited conversations with intelligent auto-summarization
• Your Data, Your Control - 100% local storage with zero cloud dependencies or privacy concerns
• Effortless Organization - Per-project memory slots with timeline navigation and smart tagging
• Intelligent Merging - Automatically combines related conversations while eliminating duplicates

Keeping Memcord Updated

cd /path/to/memcord
git pull
uv pip install -e .
uv run python scripts/generate-config.py  # Regenerate configs

# Optional: Enable auto-save hooks (new in v2.5.0)
uv run python scripts/generate-config.py --install-hooks

The --install-hooks flag is idempotent — it merges into existing .claude/settings.json without overwriting other settings or hooks.

Using Memcord

First-Time Setup (New Project)

# 1. Once you are in claude code, initialize the project with a memory slot (one-time setup)
memcord_init "." "my-project-name"
# OR
memcord_init "my_project_name"
# Creates .memcord file containing "my-project-name"

# 2. Start saving your conversations
/memcord-save-progress  # Auto-detects slot from .memcord file

Subsequent Sessions (Returning to Project)

# Just use slash commands - no slot name needed!
/memcord-read           # Reads from bound slot
/memcord-save           # Saves to bound slot
/memcord-save-progress  # Summarizes and saves

Saving, Searching & Querying (Direct Tool Calls)

memcord_name "project_meeting"          # Create or select a slot (outside a bound project)
memcord_save "Our discussion about..."  # Save exact text
memcord_save_progress                   # Save a compressed summary
memcord_read                            # Read the slot

memcord_select_entry "2 hours ago"    # Jump to a point in the timeline
memcord_list                          # List all slots
memcord_search "API design"           # Full-text search
memcord_query "What did we decide?"   # Natural language query

memcord_zero                          # Privacy mode — nothing gets saved

See Complete Tools Reference for all 23 tools with full parameters and examples.

Enable Auto-Save (Optional)

uv run python scripts/generate-config.py --install-hooks

Automatically saves conversation progress before context compaction and on session end. See config-templates/README.md for details.

How Auto-Detection Works

All read and write operations follow the same slot resolution priority:

1. Explicit slot_name argument (always wins)
2. Currently active slot (set by memcord_use or memcord_name)
3. .memcord binding file in the current working directory

When the .memcord binding is used and the slot already exists, it is also auto-activated for the rest of the session — so subsequent operations skip re-detection automatically.

This means after memcord_init, a fresh session (no memcord_use call needed) will correctly route memcord_save, memcord_save_progress, memcord_configure, and memcord_read to the bound slot.

Custom Storage Path

Point a slot's data file at any directory — e.g. a Dropbox/OneDrive folder — to share it across devices, via memcord_configure. Once linked, the slot's settings (summarizer backend, etc.) travel with the data too, so every device sharing the folder sees the same configuration.

New memory in an external path:

memcord_name "shared_slot"
memcord_configure action="set" key="custom_storage_path" value="D:\Dropbox\shared"
memcord_save "..."   # writes directly to the external path

Migrate an existing memory:

memcord_configure action="set" key="custom_storage_path" value="D:\Dropbox\shared"
# Existing data is moved automatically — memcord_read/memcord_list keep working

Each device needs to run the set command once with its own local path to the shared folder. See Tools Reference — memcord_configure for migration/collision details.

Summarizer Backends

Memcord supports four pluggable summarizer backends (nltk, sumy, semantic, transformers), switchable per slot via memcord_configure action="set" key="summarizer_backend" value="..." — no restart required. New slots default to sumy (no downloads); existing slots keep nltk for backward compatibility.

See Tools Reference — memcord_configure and Features Guide for the full backend comparison, install instructions, and the MEMCORD_SUMMARIZER env var override.

Documentation

If you find this project helpful, consider:

• ⭐ Starring the repository on GitHub
• ☕ Support Development
• 🐛 Reporting bugs and suggesting features

MIT License - see LICENSE file for details.

Star History

Prerequisites

• Python 3.10+ — python.org

• uv (Python package manager) — install with:

  macOS / Linux:

  Copy & paste — that's itCopy

  curl -LsSf https://astral.sh/uv/install.sh | sh

  Windows (PowerShell):

  Copy & paste — that's itCopy

  powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Quick Start

macOS / Linux:

curl -fsSL https://github.com/ukkit/memcord/raw/main/install.sh | bash

Windows (PowerShell):

irm https://github.com/ukkit/memcord/raw/main/install.ps1 | iex

This will:

• ✅ Download and setup memcord
• ✅ Set up Python virtual environment using uv
• ✅ Generate platform-specific MCP configuration files
• ✅ Configure Claude Desktop, Claude Code, VSCode, and Antigravity IDE

IDE Configuration

The installer auto-configures all supported IDEs. For manual setup or troubleshooting, see the detailed guides:

Manual Installation

git clone https://github.com/ukkit/memcord.git
cd memcord
uv venv && uv pip install -e .
uv run python scripts/generate-config.py

See the Complete Installation Guide for updating, advanced options, and custom commands.