copilot-mem

🧠 Copilot-Mem

Persistent memory for GitHub Copilot — never lose context across chat sessions again.

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Inspired by claude-mem, copilot-mem brings persistent memory to the GitHub Copilot ecosystem. It automatically captures, compresses, and retrieves context across coding sessions — so Copilot remembers your past decisions, debugging insights, and project conventions.

Features

• Persistent Memory — Seamlessly preserves context across Copilot Chat sessions
• Auto-Capture — Automatically records chat messages, file edits, and tool usage
• Full-Text Search — SQLite FTS5-powered search with BM25 ranking
• MCP Integration — 5 MCP tools that Copilot can call directly for memory retrieval
• Progressive Disclosure — Token-efficient retrieval: search → timeline → full details (~10x savings)
• Privacy First — All data local, .copilot-mem-ignore support, <private> tag stripping
• Web Viewer — Browse, search, and manage memories at localhost:37888/ui
• VS Code Extension — One-click install with auto-capture and context injection

Architecture

┌─────────────────────────────────────────────────────┐
│                   VS Code Extension                  │
│              (copilot-mem)                           │
│                                                      │
│  ┌──────────────┐  ┌─────────────┐  ┌────────────┐ │
│  │ Auto-Capture  │  │ Auto-Config │  │  Commands  │ │
│  │ (chat events, │  │ (MCP server │  │  (save,    │ │
│  │  file edits)  │  │  registration│  │  viewer)   │ │
│  └──────┬───────┘  └─────────────┘  └────────────┘ │
└─────────┼───────────────────────────────────────────┘
          │
          ▼
┌─────────────────────────────────────────────────────┐
│              MCP Server + HTTP API                   │
│         (@copilot-mem/mcp-server)                    │
│                                                      │
│  MCP Tools:              HTTP API (port 37888):     │
│  • search                • POST /capture            │
│  • timeline              • GET  /api/sessions       │
│  • get_memories          • GET  /api/observations   │
│  • save_memory           • GET  /api/search         │
│  • smart_search          • GET  /ui                 │
└─────────┬───────────────────────────────────────────┘
          │
          ▼
┌─────────────────────────────────────────────────────┐
│                   Core Library                       │
│             (@copilot-mem/core)                      │
│                                                      │
│  ┌──────────┐  ┌───────────┐  ┌──────────────────┐ │
│  │ Storage   │  │ Config    │  │ Search Engine    │ │
│  │ (SQLite   │  │ (~/.      │  │ (FTS5 + BM25    │ │
│  │  + WAL)   │  │ copilot-  │  │  ranking)        │ │
│  │           │  │ mem/)     │  │                  │ │
│  └──────────┘  └───────────┘  └──────────────────┘ │
└─────────────────────────────────────────────────────┘

Installation

Via npm (MCP server only)

npm install -g @copilot-mem/mcp-server

Then add to your VS Code .vscode/mcp.json:

{
  "servers": {
    "copilot-mem": {
      "type": "stdio",
      "command": "copilot-mem-server"
    }
  }
}

Via VS Code Extension (recommended)

Coming soon to VS Code Marketplace

Install the extension, and it will:

1. Auto-start the MCP server
2. Register itself with Copilot
3. Begin capturing chat events automatically

MCP Tools

Tool	Description	Token Cost
search	Query memories by keywords, returns compact index with IDs	~50-100/result
timeline	Chronological context around specific observations	~200/result
get_memories	Fetch full details by observation ID(s)	~500-1000/result
save_memory	Manually save something important	—
smart_search	Natural language query with auto-expansion	varies

Progressive Disclosure Pattern

1. search("auth bug")           → 10 results, ~500 tokens
2. timeline(["id1", "id2"])     → surrounding context, ~400 tokens
3. get_memories(["id1"])        → full details, ~800 tokens

vs. fetching everything upfront → ~8000+ tokens

Configuration

Settings stored in ~/.copilot-mem/settings.json:

{
  "port": 37888,
  "dataDir": "~/.copilot-mem/data/",
  "autoCapture": true,
  "compressionModel": null,
  "logLevel": "info",
  "contextInjection": true,
  "maxContextTokens": 2000
}

Setting	Default	Description
port	37888	HTTP server port
dataDir	~/.copilot-mem/data/	SQLite database location
autoCapture	true	Auto-capture chat events and file edits
logLevel	"info"	Log level: debug, info, warn, error
contextInjection	true	Inject relevant memories into new sessions
maxContextTokens	2000	Max tokens for injected context

Privacy

• All data stays local — stored in ~/.copilot-mem/
• .copilot-mem-ignore — gitignore-style file to exclude paths from capture
• <private> tags — wrap sensitive content to exclude it from storage
• No telemetry — zero data sent anywhere

Web Viewer

Open http://localhost:37888/ui to browse your memories:

• View all sessions and observations
• Search with full-text search
• Delete individual memories
• View storage statistics

Development

Prerequisites

• Node.js 18+
• npm 9+

Setup

git clone https://github.com/charantejmandali18/copilot-mem.git
cd copilot-mem
npm install
npm run build
npm test

Project Structure

copilot-mem/
├── packages/
│   ├── core/           # @copilot-mem/core — storage, search, config
│   ├── mcp-server/     # @copilot-mem/mcp-server — MCP tools + HTTP API
│   └── vscode/         # copilot-mem — VS Code extension
├── docs/
│   ├── specs/          # Design specifications
│   └── conversation-context.md
├── turbo.json          # Turborepo config
└── tsconfig.base.json  # Shared TypeScript config

Scripts

npm run build          # Build all packages
npm test               # Run all tests
npm run dev            # Watch mode
npm run format         # Format code with Prettier
npm run format:check   # Check formatting

Running Locally

# Start the MCP server with HTTP API
node packages/mcp-server/dist/index.js

# Test the HTTP API
curl http://localhost:37888/api/sessions

# Save a memory
curl -X POST http://localhost:37888/capture \
  -H "Content-Type: application/json" \
  -d '[{"type":"manual","content":"Fixed auth bug in login.ts"}]'

# Search memories
curl "http://localhost:37888/api/search?q=auth+bug"

# Open web viewer
open http://localhost:37888/ui

Roadmap

• Core storage layer (SQLite + FTS5)
• MCP server with 5 tools
• HTTP API + Web viewer
• VS Code extension (auto-capture, context injection)
• AI-based compression (reduce storage, improve search)
• Chroma vector search (semantic search)
• npm package publishing
• VS Code Marketplace publishing

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License — see the LICENSE file for details.

Acknowledgments

• claude-mem by Alex Newman — the inspiration for this project
• Model Context Protocol — the protocol that makes this possible
• GitHub Copilot — the AI assistant we’re enhancing