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memcord

by ukkit·67·Score 47

Privacy-first MCP server for AI memory management with intelligent summarization and search capabilities.

ai-llmproductivitydeveloper-tools
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Overview

Memcord is a comprehensive MCP server designed for organizing and managing AI chat history with strong privacy controls. It provides tools for saving, summarizing, searching, and organizing conversations across multiple memory slots. The server supports various summarization backends including extractive methods (NLTK, Sumy) and abstractive models (transformers, semantic), allowing users to balance speed and quality based on their needs.

Try asking AI

After installing, here are 5 things you can ask your AI assistant:

you:Long-term project documentation and conversation tracking
you:Research and knowledge base building from AI conversations
you:Privacy-sensitive contexts requiring local storage
you:Where is my data stored?
you:How many summarization backends are available?

When to choose this

Choose Memcord when you need to preserve conversation context across multiple AI sessions with complete privacy control and local storage.

When NOT to choose this

Don't choose Memcord if you need cloud-based AI memory services or require team collaboration features across different users.

Tools this server exposes

11 tools extracted from the README
  • memcord_namememcord_name(slot_name: string)

    Create or select a memory slot for storing conversations

  • memcord_savememcord_save(text: string)

    Save exact text to the current memory slot

  • memcord_save_progressmemcord_save_progress()

    Save a compressed summary of current conversation

  • memcord_readmemcord_read(slot_name: string = null)

    Read contents from the current memory slot

  • memcord_select_entrymemcord_select_entry(timestamp: string)

    Navigate to a specific point in the conversation timeline

  • memcord_listmemcord_list()

    List all available memory slots

  • memcord_searchmemcord_search(query: string)

    Full-text search across all memory contents

  • memcord_querymemcord_query(question: string)

    Ask natural language questions about saved conversations

  • memcord_initmemcord_init(path: string, slot_name: string)

    Bind a memory slot to the current directory

  • memcord_zeromemcord_zero()

    Enable privacy mode to prevent saving conversations

  • memcord_configurememcord_configure(action: string, key: string = null, value: string = null)

    Configure settings for memory slots

Comparable tools

memo-mcpchat-memorysession-history

Installation

Quick Install

**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

Claude Desktop Configuration

After installation, Memcord will automatically configure Claude Desktop. The configuration file will be placed in your Claude settings directory:

{
  "mcpServers": {
    "memcord": {
      "command": "python",
      "args": ["-m", "memcord.server"]
    }
  }
}

FAQ

Where is my data stored?
All data is stored locally on your device in your home directory under ~/.memcord. Nothing is sent to the cloud.
How many summarization backends are available?
Memcord supports four backends: NLTK (fast, extractive), Sumy (fast, graph-based extractive), Semantic (medium speed, best extractive), and Transformers (slow, best abstractive quality).

Compare memcord with

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Last updated · Auto-generated from public README + GitHub signals.