ai-ml

Memory Plus

yuchen20

by yuchen20

Memory Plus is a lightweight, local RAG memory store for MCP agents to record, manage, and visualize persistent memories

Lightweight, local RAG memory store for MCP agents. Easily record, retrieve, update, delete, and visualize persistent "memories" across sessions.

github stars

52

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Local storage — no cloud dependencyInteractive graph visualizationMemory versioning and history tracking

best for

  • / AI agents that need to remember context between conversations
  • / Personal knowledge management and note-taking
  • / Building AI assistants with long-term memory

capabilities

  • / Record and store persistent memories across sessions
  • / Search memories by keywords or topics
  • / Update and modify existing memory entries
  • / Import documents directly into memory
  • / Visualize memory relationships with interactive graphs
  • / Track memory versions and history

what it does

A local RAG memory store that lets MCP agents save, search, and recall persistent memories (notes, context, ideas) across sessions. Includes visualization of memory relationships through interactive graph clusters.

about

Memory Plus is a community-built MCP server published by yuchen20 that provides AI assistants with tools and capabilities via the Model Context Protocol. Memory Plus is a lightweight, local RAG memory store for MCP agents to record, manage, and visualize persistent memories It is categorized under ai ml.

how to install

You can install Memory Plus in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

Apache-2.0

Memory Plus is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

![memory_plus](https://memory-plus.imgix.net/memory_plus.png) ![pretty image](https://memory-plus.imgix.net/memory_server_banner.png) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](./LICENSE) ![visitors](https://visitor-badge.laobi.icu/badge?page_id=Yuchen20.Memory-Plus) [![PyPI version](https://badge.fury.io/py/memory-plus.svg)](https://pypi.org/project/memory-plus/) [![PyPI Downloads](https://static.pepy.tech/badge/memory-plus)](https://pepy.tech/projects/memory-plus) # Memory-Plus A lightweight, local Retrieval-Augmented Generation (RAG) memory store for MCP agents. Memory-Plus lets your agent record, retrieve, update, and visualize persistent "memories"—notes, ideas, and session context—across runs. > 🏆 **First Place** at the [Infosys Cambridge AI Centre Hackathon](https://infosys-cam-ai-centre.github.io/Infosys-Cambridge-Hackathon/)! ## Key Features * **Record Memories**:Save user data, ideas, and important context. * **Retrieve Memories**:Search by keywords or topics over past entries. * **Recent Memories**:Fetch the last *N* items quickly. * **Update Memories**:Append or modify existing entries seamlessly. * **Visualize Memories**:Interactive graph clusters revealing relationships. * **File Import** (*since v0.1.2*):Ingest documents directly into memory. * **Delete Memories** (*since v0.1.2*):Remove unwanted entries. * **Memory for Memories** (*since v0.1.4*):Now we use `resources` to teach your AI exactly when (and when not) to recall past interactions. * **Memory Versioning** (*since v0.1.4*):When memories are updated, we keep the old versions to provide a full history. --- ![alt text](https://memory-plus.imgix.net/memory_visualization.png) ## Installation ### 1. Prerequisites **Google API Key** Obtain from [Google AI Studio](https://aistudio.google.com/apikey) and set as `GOOGLE_API_KEY` in your environment. > Note that we will only use the `Gemini Embedding API` with this API key, so it is **Entirely Free** for you to use!
Setup Google API Key Example ```bash # macOS/Linux export GOOGLE_API_KEY="" # Windows (PowerShell) setx GOOGLE_API_KEY "" ```
**UV Runtime** Required to serve the MCP plugin.
Install UV Runtime ```bash pip install uv ``` Or install via shell scripts: ```bash # macOS/Linux curl -LsSf https://astral.sh/uv/install.sh | sh # Windows (PowerShell) powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" ```
### VS Code One-Click Setup Click the badge below to automatically install and configure Memory-Plus in VS Code: [![One Click Install in VS Code](https://img.shields.io/badge/VS_Code-UV-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=memory-plus&config=%7B%22command%22%3A%22uvx%22%2C%22args%22%3A%5B%22-q%22%2C%22memory-plus%40latest%22%5D%7D) This will add the following to your `settings.json`: ```json { "mcpServers": { //..., your other MCP servers "memory-plus": { "command": "uvx", "args": [ "-q", "memory-plus@latest" ], } } } ``` For `cursor`, go to `file -> Preferences -> Cursor Settings -> MCP` and add the above config. If you didn't add the `GOOGLE_API_KEY` to your secrets / environment variables, you can add it with: ```json "env": { "GOOGLE_API_KEY": "" } ``` just after the `args` array with in the `memory-plus` dictionary. For `Cline` add the following to your `cline_mcp_settings.json`: ```json { "mcpServers": { //..., your other MCP servers "memory-plus": { "disabled": false, "timeout": 300, "command": "uvx", "args": [ "-q", "memory-plus@latest" ], "env": { "GOOGLE_API_KEY": "${{ secrets.GOOGLE_API_KEY }}" }, "transportType": "stdio" } } } ``` For other IDEs it should be mostly similar to the above. ## Local Testing and Development Using MCP Inspector, you can test the memory-plus server locally. ```bash git clone https://github.com/Yuchen20/Memory-Plus.git cd Memory-Plus npx @modelcontextprotocol/inspector fastmcp run run .\memory_plus\mcp.py ``` Or If you prefer using this MCP in an actual Chat Session. There is a template chatbot in `agent.py`. ```bash # Clone the repository git clone https://github.com/Yuchen20/Memory-Plus.git cd Memory-Plus # Install dependencies pip install uv uv pip install fast-agent-mcp uv run fast-agent setup ``` setup the `fastagent.config.yaml` and `fastagent.secrets.yaml` with your own API keys. ```bash # Run the agent uv run agent_memory.py ``` ## RoadMap - [x] Memory Update - [x] Improved prompt engineering for memory recording - [x] Better Visualization of Memory Graph - [x] File Import - [ ] Remote backup! - [ ] Web UI for Memory Management > If you have any feature requests, please feel free to add them by adding a new issue or by adding a new entry in the [Feature Request](https://voltaic-shell-9af.notion.site/1f84e395c1d18059849ce844fcbba903?pvs=105) ## License This project is licensed under the **Apache License 2.0**. See [LICENSE](./LICENSE) for details. ## FAQ ### 1. Why is memory-plus not working? - Memory-plus has a few dependencies that can be slow to download the first time. It typically takes around 1 minute to fetch everything needed. - Once dependencies are installed, subsequent usage will be much faster. - If you experience other issues, please feel free to open a new issue on the repository. ### 2. How do I use memory-plus in a real chat session? - Simply add the MCP JSON file to your MCP setup. - Once added, memory-plus will automatically activate when needed.

FAQ

What is the Memory Plus MCP server?
Memory Plus is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Memory Plus?
This profile displays 56 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.656 reviews
  • Zaid Johnson· Dec 28, 2024

    Memory Plus has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Dhruvi Jain· Dec 20, 2024

    Memory Plus reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Kaira Jain· Dec 16, 2024

    Memory Plus is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Emma Ramirez· Dec 12, 2024

    Memory Plus reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Emma Sanchez· Dec 12, 2024

    Memory Plus is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Soo Haddad· Nov 19, 2024

    We evaluated Memory Plus against two servers with overlapping tools; this profile had the clearer scope statement.

  • Oshnikdeep· Nov 11, 2024

    I recommend Memory Plus for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Xiao Mensah· Nov 11, 2024

    We wired Memory Plus into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Aarav Agarwal· Nov 7, 2024

    According to our notes, Memory Plus benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Emma Abbas· Nov 3, 2024

    I recommend Memory Plus for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

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