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aitytech/agentkits-memory

by Various

Persistent memory system for AI coding assistants via MCP. Works with Claude Code, Cursor, Copilot, Windsurf, Cline.

A

MCP

aitytech/agentkits-memory

Added 1 June 2026

Overview

A persistent memory system for AI coding assistants that operates via the Model Context Protocol (MCP). It integrates with tools like Claude Code, Cursor, Copilot, Windsurf, and Cline to maintain context across sessions.

Best for

Best for
Developers using multiple AI coding assistants who need persistent session memory

Use cases

  • Keep chat history and project knowledge alive between Claude Code sessions
  • Provide consistent context for Cursor agent across multiple tasks
  • Enable long-running memory for Cline workflows

How to use

Install

npx @aitytech/agentkits-memory web

Tools exposed

  • memory_status
  • memory_save
  • memory_search
  • memory_timeline
  • memory_details
  • memory_recall
  • memory_list
  • memory_update
  • memory_delete
  • session-init
  • user-message
  • embed-session
  • enrich-session
  • compress-session

Tested with

Claude Code, Cursor, Windsurf, Cline, ChatGPT

Notes

A persistent memory system for AI coding assistants that operates via the Model Context Protocol (MCP). It integrates with tools like Claude Code, Cursor, Copilot, Windsurf, and Cline to maintain context across sessions.

61 stars on GitHub. Last updated 2026-02-27. Licensed MIT.

Use cases

  • Keep chat history and project knowledge alive between Claude Code sessions
  • Provide consistent context for Cursor agent across multiple tasks
  • Enable long-running memory for Cline workflows

Pros

  • Works with multiple popular coding assistants
  • Lightweight MCP-based integration
  • Written in TypeScript for easy maintenance

Cons

  • Small community with 61 GitHub stars
  • Requires MCP setup and configuration
  • Limited to supported MCP-compatible tools

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Works with multiple popular coding assistants
  • Lightweight MCP-based integration
  • Written in TypeScript for easy maintenance

Cons

  • Small community with 61 GitHub stars
  • Requires MCP setup and configuration
  • Limited to supported MCP-compatible tools
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