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README.md
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---
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title: Project Memory - MCP-Powered Team Memory System
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emoji: ๐ง
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colorFrom: blue
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colorTo: purple
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sdk: docker
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app_port: 7860
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pinned: false
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license: mit
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short_description: AI-powered shared memory for development teams using MCP
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tags:
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- building-mcp-track-enterprise
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---
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# ProjectMemory - MCP 1st Birthday Hackathon Submission
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Check out the Hackathon details at: https://huggingface.co/MCP-1st-Birthday
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## ๐ฏ Track 1: Building MCP - Enterprise Category
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**Project Memory** is a multi-user, multi-project AI memory system powered by MCP (Model Context Protocol). It creates shared project memory where every action gets logged and becomes searchable via semantic search and AI chat.
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## ๐ What We Built
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An MCP server that extends LLM capabilities for enterprise teams by:
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- **Persistent Project Memory**: Every task completion generates AI documentation that becomes searchable knowledge
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- **Semantic Search**: Vector-based memory retrieval across all project activities
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- **MCP Tool Integration**: Exposes project management capabilities as MCP tools
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- **Multi-User Collaboration**: Teams can share and search collective knowledge
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## ๐ ๏ธ MCP Tools Exposed
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Our MCP server provides these tools:
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- `create_project`: Initialize a new project workspace
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- `list_projects`: View all available projects
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- `join_project`: Join an existing project
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- `list_tasks`: Get project tasks with status
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- `complete_task`: Mark task as done with AI-generated documentation
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- `memory_search`: Semantic search across project history
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- `list_activity`: View project activity feed
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## ๐น Demo Video
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[Watch our 3-minute demo showing MCP integration with Claude Desktop](#) *(link to be added)*
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## ๐๏ธ Architecture
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```
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โโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโ
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โ Web Frontend โโโโโโถโ FastAPI Backend โ
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โ (React) โ โ (MCP Client) โ
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โโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโ
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โ
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โผ
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โโโโโโโโโโโโโโโโโโโ
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โ MCP Server โ
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โ (TypeScript) โ
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โโโโโโโโโโโโโโโโโโโ
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โ
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โผ
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โโโโโโโโโโโโโโโโโโโ
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โ SQLite + Vec โ
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โ (Embeddings) โ
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โโโโโโโโโโโโโโโโโโโ
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```
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## ๐ก Key Features
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1. **Task Completion Pipeline**: Transforms user work into searchable documentation
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2. **Vector Search**: Semantic retrieval using sqlite-vec embeddings
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3. **Chat Interface**: Natural language queries using MCP tools
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4. **Activity Feed**: Real-time project activity tracking
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5. **Multi-Project Support**: Manage multiple projects with isolated memory
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## ๐ง Technical Stack
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- **MCP Server**: TypeScript with @modelcontextprotocol/sdk
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- **Backend**: FastAPI (Python) as MCP client
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- **Frontend**: React + Vite + Tailwind CSS
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- **Database**: SQLite with sqlite-vec for embeddings
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- **AI**: Google Generative AI (Gemini) for documentation generation
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- **Deployment**: Docker container for Hugging Face Spaces
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## ๐ฎ How to Use
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1. **Create or Join a Project**: Start by creating a new project or joining an existing one
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2. **Complete Tasks**: Mark tasks as done and provide context about your work
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3. **AI Documentation**: System automatically generates searchable documentation
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4. **Search Memory**: Use semantic search to find any past work or decision
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5. **Chat with Memory**: Ask questions about project history using natural language
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## ๐ข Deployment
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This Space runs as a Docker container combining:
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- FastAPI backend serving as MCP client
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- React frontend for user interface
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- MCP server handling all tool operations
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- SQLite database with vector search capabilities
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## ๐ Environment Variables
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Configure in Space settings:
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- `GOOGLE_API_KEY`: For Gemini AI integration
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- `DATABASE_URL`: (Optional) Custom database connection
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## ๐ฅ Team
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*Add team member names here*
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## ๐ License
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MIT License - See LICENSE file for details
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## ๐ Links
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- [GitHub Repository](https://github.com/YOUR_USERNAME/project-memory)
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- [MCP Documentation](https://modelcontextprotocol.io)
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- [Hackathon Page](https://huggingface.co/MCP-1st-Birthday)
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