SelfHub MCP Server

Your Personal AI Memory Hub - Store and retrieve your personal data from any MCP-enabled AI assistant.

🎯 What is SelfHub?

SelfHub is a Model Context Protocol (MCP) server that acts as your personal digital memory. Store notes, preferences, code snippets, tasks, and any information you want - then access them seamlessly from any AI assistant that supports MCP (Claude Desktop, VS Code Copilot, etc.).

Think of it as your personal knowledge base that travels with you across all AI conversations.

Step 2: Configure Claude Desktop

Open the Claude Desktop configuration file:

• Windows: %APPDATA%\Claude\claude_desktop_config.json

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

• Linux: ~/.config/Claude/claude_desktop_config.json

Add this configuration (replace with your actual path):

{
  "mcpServers": {
    "selfhub": {
      "command": "node",
      "args": ["C:\\absolute\\path\\to\\SelfHub\\build\\index.js"]
    }
  }
}

Important for Windows: Use double backslashes (\\) in the path!

Step 3: Restart Claude Desktop

Completely quit and restart Claude Desktop.

Step 4: Test It!

In Claude, try:

• "List all my memories"

• "Search my memories for typescript"

• "Store that I prefer dark mode in all applications"

💻 Setup with VS Code

Step 1: Build the Server

pnpm build

Step 2: Configure VS Code

The workspace is already configured! Just reload VS Code:

Press Ctrl+Shift+P (or Cmd+Shift+P on Mac) → Type "Reload Window" → Press Enter

Step 3: Test in Copilot Chat

Open GitHub Copilot Chat (Ctrl+Alt+I) and try:

@workspace list my memories
@workspace search my memories for "typescript"
@workspace store in my memory: I love using pnpm for package management

Note: You need GitHub Copilot extension installed and enabled.

🛠️ Available Tools

Memory Management (5 tools)

1. store_memory

Store new information in your memory hub.

Example:

Store that I prefer TypeScript over JavaScript for all new projects

Parameters:

• content (required) - The information to store

• type - Memory type: short-term, long-term, contextual

• category - Category: personal, professional, learning, projects, code, tasks, etc.

• title - Optional title

• tags - Array of tags

• importance - 1-5 importance level

2. retrieve_memory

Get a specific memory by its ID.

Example:

Retrieve memory mem_001

3. list_memories

List memories with optional filters.

Example:

List all my professional memories
Show me memories tagged with 'typescript'
List memories sorted by importance

Parameters:

• type - Filter by type

• category - Filter by category

• tags - Filter by tags

• contextId - Filter by context

• limit - Max results (default: 50)

• offset - Pagination offset

• sortBy - Sort field: createdAt, updatedAt, importance, accessCount

• sortOrder - asc or desc

4. search_memories

Search through your memories using text queries.

Example:

Search my memories for "typescript"
Find memories about "API design"

Parameters:

• query (required) - Search query

• category - Filter by category

• type - Filter by type

• tags - Filter by tags

• limit - Max results (default: 10)

5. delete_memory

Delete a memory by ID.

Example:

Delete memory mem_005

Context Management (3 tools)

6. create_context

Create a new organizational context.

Example:

Create a new context called "Machine Learning Project" for project type

Parameters:

• name (required) - Context name

• type (required) - conversation, project, topic, temporal

• description - Optional description

• tags - Array of tags

• memoryIds - Initial memory IDs to include

7. activate_context

Activate a context and load its memories.

Example:

Activate the "SelfHub Development" context

8. list_contexts

List all contexts with optional filters.

Example:

List all my project contexts
Show active contexts

Analytics (1 tool)

9. get_stats

Get usage statistics and insights.

Example:

Show me my memory statistics

Returns:

• Total memories count

• Memories by type breakdown

• Memories by category breakdown

• Total contexts

• Most used tags

📚 Example Usage Scenarios

Personal Knowledge Management

Store that I prefer dark mode in all applications
Store my favorite TypeScript coding conventions
Remember that I use pnpm for package management
Search my memories for "preferences"

Project Development

Create a new context called "SelfHub Development" for project type
Store in SelfHub context: Database schema uses Drizzle ORM
Activate the SelfHub Development context
List all memories in the SelfHub context

Learning & Notes

Store as learning: Vector embeddings represent text as numerical arrays
Tag with "machine-learning" and "embeddings"
Search my learning memories for "embeddings"
List all my learning-related memories sorted by date

Code Snippets

Store this code snippet: const sum = (a, b) => a + b
Category: code, Tags: javascript, utility
Search my code for "utility functions"

🗂️ Sample Data

SelfHub comes with 6 pre-loaded sample memories:

1. mem_001 - Dark mode UI preference (personal)

2. mem_002 - TypeScript coding standard (professional)

3. mem_003 - Vector embeddings concept (learning)

4. mem_004 - SelfHub project overview (projects)

5. mem_005 - Database development task (tasks)

6. mem_006 - ID generation utility code (code)

And 2 sample contexts:

1. ctx_001 - SelfHub Development (project)

2. ctx_002 - AI & Machine Learning (topic)

🏗️ Project Structure

SelfHub/
├── src/
│   ├── index.ts              # Main MCP server
│   ├── models/               # TypeScript type definitions
│   │   ├── memory.model.ts
│   │   ├── context.model.ts
│   │   └── index.ts
│   ├── services/             # Business logic layer
│   │   ├── memory.service.ts
│   │   └── context.service.ts
│   └── storage/              # Storage implementation
│       └── mock-storage.ts   # In-memory mock data
├── build/                    # Compiled JavaScript output
├── .github/                  # GitHub Actions CI/CD
│   └── workflows/
│       ├── ci.yml           # Continuous Integration
│       └── release.yml      # Automated releases
├── .vscode/                 # VS Code configuration
│   └── settings.json        # MCP server settings
├── package.json
├── tsconfig.json
└── README.md

🔧 Development

Available Scripts

# Development mode (auto-reload with tsx)
pnpm dev

# Type checking
pnpm typecheck

# Build for production
pnpm build

# Clean build directory
rm -rf build

How It Works

1. MCP Server (src/index.ts) - Implements the MCP protocol, defines 9 tools

2. Services Layer - Business logic for memory and context operations

3. Storage Layer - In-memory Map-based storage with sample data

4. Models - TypeScript interfaces for type safety

Testing Locally

# Start the server
pnpm dev

# You should see:
# 🚀 SelfHub MCP Server running with mock data!
# 📊 Loaded 6 sample memories and 2 sample contexts
# 🛠️  Available tools: 9

The server runs on stdio (standard input/output) and waits for MCP protocol messages. You cannot interact with it directly - it needs an MCP client like Claude Desktop or VS Code.

🐛 Troubleshooting

Server Not Showing in Claude Desktop

1. Check the config path:

   • Make sure you're editing the correct config file

   • Use absolute path, not relative

2. Verify build exists:

   ls build/index.js

3. Check for typos:

   • Windows paths need double backslashes: C:\\path\\to\\

   • JSON syntax must be valid

4. Restart Claude completely:

   • Quit from system tray

   • Wait a few seconds

   • Start again

5. Check Claude logs:

   • Windows: %APPDATA%\Claude\logs

   • macOS: ~/Library/Logs/Claude

VS Code Not Showing Tools

1. Make sure GitHub Copilot is installed:

   • Press Ctrl+Shift+X

   • Search "GitHub Copilot"

   • Install both "GitHub Copilot" and "GitHub Copilot Chat"

2. Reload VS Code window:

   • Ctrl+Shift+P → "Reload Window"

3. Check the build:

   pnpm build

Build Errors

# Clean and rebuild
rm -rf build node_modules
pnpm install
pnpm build

Data Not Persisting

This is expected! The current version uses in-memory storage. All data resets when you restart the server. This is intentional for the initial version - persistent storage will be added in a future update.

🚀 CI/CD

This project includes GitHub Actions workflows:

• CI Pipeline - Runs on every push, tests on Node 18.x and 20.x

• Release Workflow - Creates releases when you push version tags

• Dependabot - Automatically updates dependencies

See .github/workflows/ for details.

📖 Documentation

• Model Context Protocol - Learn about MCP

• Claude Desktop - Download Claude Desktop

• GitHub Copilot - Learn about Copilot

🗺️ Roadmap

Current Version (v0.1.0)

• ✅ In-memory storage

• ✅ 9 MCP tools

• ✅ Memory categorization and tagging

• ✅ Context management

• ✅ Text-based search

• ✅ Sample data

Future Enhancements

• Persistent SQLite storage

• Vector embeddings for semantic search

• File import/export (JSON, Markdown, CSV)

• Data encryption for sensitive information

• Web UI for management

• Multi-user support

• Cloud sync

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

MIT License - see LICENSE file for details.

💬 Support

If you have questions or run into issues:

1. Check the Troubleshooting section

2. Review the documentation above

3. Open an issue on GitHub

🌟 Acknowledgments

Built with:

• Model Context Protocol SDK - MCP implementation

• TypeScript - Type safety

• pnpm - Fast package manager

Made with ❤️ by Sagargupta16

Your personal AI memory hub - remember everything, access anywhere!