| --- |
| title: Long Term Memory MCP Server |
| emoji: 🧠 |
| colorFrom: blue |
| colorTo: purple |
| sdk: gradio |
| sdk_version: "4.0.0" |
| app_file: app.py |
| pinned: false |
| license: mit |
| tags: |
| - mcp-server-track |
| - mcp |
| - memory |
| - rag |
| - llm |
| - conversation |
| short_description: MCP Server providing long-term memory for LLM conversations |
| --- |
| |
| # 🧠 Long Term Memory MCP Server |
|
|
| **Tags**: mcp-server-track |
|
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| A Model Context Protocol (MCP) server that provides long-term memory capabilities for LLM conversations. This allows users to save important insights, conclusions, and context from conversations and retrieve them in future interactions. |
|
|
| ## 🎯 Problem Solved |
|
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| Current LLM interactions are stateless - they don't remember previous conversations or insights you've shared. This MCP server solves that by providing: |
|
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| - **Persistent Memory**: Save important insights and context from conversations |
| - **Semantic Search**: Find relevant memories using natural language queries |
| - **Context Continuity**: Build upon previous conversations and learnings |
| - **Knowledge Accumulation**: Build a personal knowledge base over time |
|
|
| ## 🚀 Features |
|
|
| ### MCP Server Tools |
| - `save_memory` - Save insights, conclusions, or context to long-term memory |
| - `search_memory` - Search through memories using semantic similarity |
| - `list_memories` - Browse all stored memories |
| - `delete_memory` - Remove specific memories |
|
|
| ### Gradio Demo Interface |
| - Interactive web interface for testing all MCP tools |
| - Real-time memory statistics |
| - Semantic search with adjustable similarity thresholds |
| - Memory browsing and management |
|
|
| ## 🛠️ Technical Architecture |
|
|
| - **MCP Protocol**: Standards-compliant MCP server |
| - **Vector Storage**: ChromaDB for efficient semantic search |
| - **Embeddings**: SentenceTransformers (all-MiniLM-L6-v2) for semantic understanding |
| - **Interface**: Gradio web app for demonstration and testing |
| - **Storage**: Persistent local database |
|
|
| ## 📦 Installation & Usage |
|
|
| ### Local Development |
| ```bash |
| # Clone and install dependencies |
| pip install -r requirements.txt |
| |
| # Run the application |
| python app.py |
| ``` |
|
|
| ### Hugging Face Spaces |
| This Space runs both the MCP server and Gradio demo simultaneously. |
|
|
| ## 🎮 Demo Video |
|
|
| - |
|
|
| ## 💡 Use Cases |
|
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| ### Example Scenario |
| 1. **Initial Conversation**: You discuss quantum consciousness theories with an LLM |
| 2. **Save Insight**: Use `save_memory` to store key conclusions |
| 3. **Future Conversation**: LLM can `search_memory` to find relevant context |
| 4. **Continuity**: Build upon previous insights in new discussions |
|
|
| ### Sample Usage with Claude Desktop |
|
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| **Saving a memory:** |
| ``` |
| User: "Save this insight to memory: 'Consciousness might emerge from quantum processes in microtubules, as proposed by Penrose-Hameroff theory. This could explain the hard problem of consciousness.' Title: 'Quantum Consciousness Theory', Tags: 'consciousness, quantum, penrose, microtubules'" |
| |
| LLM: *Uses save_memory tool* |
| ✅ Memory saved successfully! ID: abc123... |
| ``` |
|
|
| **Searching memories:** |
| ``` |
| User: "What did we previously discuss about consciousness and quantum physics?" |
| |
| LLM: *Uses search_memory tool* |
| 🔍 Found relevant memory: "Quantum Consciousness Theory" - discusses how consciousness might emerge from quantum processes in microtubules... |
| ``` |
|
|
| ## 🔧 MCP Client Configuration |
|
|
| ### Claude Desktop |
| Add to your `claude_desktop_config.json`: |
| ```json |
| { |
| "mcpServers": { |
| "long-term-memory": { |
| "command": "python", |
| "args": ["path/to/mcp_server.py"], |
| "env": {} |
| } |
| } |
| } |
| ``` |
|
|
| ### Cursor IDE |
| Configure in your MCP settings to connect to the server. |
|
|
| ## 📊 Memory Statistics |
|
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| The system tracks: |
| - Total memories stored |
| - Content length statistics |
| - Tag usage patterns |
| - Timestamp-based organization |
|
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| ## 🔐 Privacy & Data |
|
|
| - All data stored locally in ChromaDB |
| - No external API calls for embeddings (uses local SentenceTransformers) |
| - Full control over your memory data |
| - Easy export/import capabilities |
|
|
| ## 🚧 Future Enhancements |
|
|
| - [ ] Memory categorization and hierarchical organization |
| - [ ] Conversation threading and context linking |
| - [ ] Export/import functionality |
| - [ ] Advanced search filters (date, tags, content type) |
| - [ ] Memory summarization and consolidation |
| - [ ] Integration with external knowledge bases |
|
|
| ## 🤝 Contributing |
|
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| This project was created for the [Hugging Face MCP Hackathon](https://huggingface.co/Agents-MCP-Hackathon). Contributions welcome! |
|
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| ## 📝 License |
|
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| MIT License - Feel free to use and modify! |
|
|
| ## Author |
| - [Andrei Zagrebin] (@cheeeaaat) |
| --- |
|
|
| *Built with ❤️ for the Hugging Face MCP Hackathon - Track 1: MCP Server/Tool* |
