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  1. Home
  2. 🧠 Knowledge & Memory
  3. Memcord
Memcord logo
Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 4:16:16 PM

Memcord

User RatingsBe the first to rate and review this MCP server!
View Repository73 GitHub StarsTotal stargazers on GitHub for the source repository (73 stars).Visit Website

Self-hosted MCP server for organizing, searching, and AI-summarizing chat history with local storage and privacy.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet β€” we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself β€” its README, its docs, or a verified owner. We haven’t found those for ukkit/memcord, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Install Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Overview

This MCP server enables developers to maintain an organized, searchable knowledge base of chat conversations with AI-powered summarization. It supports unlimited memory through intelligent auto-summarization and stores all data locally to ensure privacy and full user control. The server provides per-project memory slots, timeline navigation, smart tagging, and automatic merging of related conversations to eliminate duplicates. It integrates with Claude Desktop, Claude Code, VSCode, and Antigravity IDE.

Use cases

β€’Organize chat history into searchable, project-based memory slots
β€’Summarize long conversations automatically to retain key context
β€’Search past chats with full-text and natural language queries
β€’Integrate chat memory with Claude and supported IDEs
β€’Maintain privacy by storing all data locally without cloud dependencies

Key features

β€’AI-powered auto-summarization of conversations
β€’Local storage with zero cloud dependencies
β€’Per-project memory slots with timeline navigation
β€’Smart tagging and intelligent merging of chat entries
β€’Command-line tools for saving, reading, searching, and querying memory

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Memcord.

Extracted Tool Capabilities
AI-powered auto-summarization of conversations
Local storage with zero cloud dependencies
Per-project memory slots with timeline navigation
Smart tagging and intelligent merging of chat entries
Command-line tools for saving, reading, searching, and querying memory

Documentation Overview

MEMCORD v4.3.6 (mcp server)

This privacy-first, self-hosted MCP server helps you organize chat history, summarize messages, search across past chats with AI β€” and keeps everything secure and fully under your control.

MCP Server Claude Code Claude Desktop VSCode Google Antigravity Python License Buy Me a Coffee

Never Lose Context Again

Transform your Claude conversations into a searchable, organized knowledge base that grows with you

What's new in v4.3.6 β€” removes two unnecessary dependencies (pandas, python-magic) from a fresh install; CSV/TSV import now uses the standard library instead of pandas.

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

Prerequisites

Python 3.10+ and uv are required. The installer handles both β€” click to expand manual instructions.
  • Python 3.10+ β€” python.org

  • uv (Python package manager) β€” install with:

    macOS / Linux:

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

    Windows (PowerShell):

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

Quick Start

macOS / Linux:

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

Windows (PowerShell):

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

This will:

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

Keeping Memcord Updated

Re-run the same installer command from Quick Start from the same folder where memcord is installed β€” it detects an existing installation and updates it in place instead of cloning a fresh copy:

macOS / Linux:

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

Windows (PowerShell):

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

This will:

  • βœ… Pull the latest changes (fast-forward only β€” aborts safely if you have local edits)
  • βœ… Reuse your existing virtual environment and upgrade dependencies
  • βœ… Regenerate MCP configuration files
  • βœ… Leave your memory data (memory_slots/) and generated configs untouched
Manual update
bash
cd /path/to/memcord
git pull
uv pip install -e . --upgrade
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 β€” it merges into existing .claude/settings.json without overwriting other settings or hooks.

Switching an Existing Install to Global Scope

Fresh installs register memcord globally (~/.claude.json) by default β€” available in every project. If you have an older install that's still project-scoped (a local .mcp.json), switch it explicitly β€” re-running the updater alone won't do this for you, since it auto-detects and preserves an existing project-scoped setup on purpose:

bash
cd /path/to/memcord
uv run python scripts/generate-config.py --scope user

Verify from a different project directory: claude mcp list should now show memcord. The original .mcp.json is left in place and still works (harmless, just redundant) β€” delete it only if you want that directory to stop pinning its own local copy instead of falling through to the global one.

Installing Slash Commands Globally

The 17 memcord-* slash commands ship in .claude/commands/ and are already usable from inside the memcord checkout the moment you clone it. To use them from any project directory, install them globally into ~/.claude/commands/:

bash
uv run python scripts/generate-config.py --manage-commands   # interactive picker
uv run python scripts/generate-config.py --commands all      # non-interactive: install all

Fresh installs prompt for this automatically (skipped when non-interactive, e.g. curl | bash). Re-run anytime to change your selection β€” only memcord's own command files are ever added or removed.

Using Memcord

First-Time Setup (New Project)

bash
# 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)

bash
# 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

Searching & Querying (Direct Tool Calls)

bash
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

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

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 β€” 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 β€” e.g. a Dropbox/OneDrive folder β€” 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:

bash
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:

bash
memcord_configure action="set" key="custom_storage_path" value="D:\Dropbox\shared"
# Existing data is moved automatically β€” 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 β€” 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="..." β€” no restart required. New slots default to sumy (no downloads); existing slots keep nltk for backward compatibility.

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

IDE Configuration

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

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
73
Stargazers on the source repository.
Last commit
1mo ago
Most recent push to the default branch.
Directory activity
1 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Memcord

Memcord requires Python 3.10 or higher and the 'uv' Python package manager, which the installer can set up automatically.

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Technical Specs & Signals

Category🧠Knowledge & Memory
More technical detailsExpand β–Ύ
Last updatedAug 7, 2026
5/6 checks healthy over the last 32d
Views1
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars73
GitHub Star CountTotal stargazers on GitHub representing community popularity (73 stars).
Last commit1mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Aug 7, 2026
44Quality signal: Fair Β· 44/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools17/30
Adoption & activity6/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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