Overview

SaveContext is a Model Context Protocol (MCP) server that gives AI coding assistants persistent memory across sessions. It combines context management, issue tracking, and project planning into a single local-first tool that works with any MCP-compatible client.

Core capabilities:

• Context & Memory — Save decisions, progress, and notes that persist across conversations
• Issue Tracking — Manage tasks, bugs, and epics with dependencies and hierarchies
• Plans & PRDs — Create specs and link them to implementation issues
• Semantic Search — Find past decisions by meaning, not just keywords
• Checkpoints — Snapshot and restore session state at any point

🛠️ Features

• Local Semantic Search: AI-powered search using Ollama or Transformers.js for offline embedding generation
• Multi-Agent Support: Run multiple CLI/IDE instances simultaneously with agent-scoped session tracking
• Automatic Provider Detection: Detects 30+ MCP clients including coding tools (Claude Code, Cursor, Cline, VS Code, JetBrains, etc.) and desktop apps (Claude Desktop, Perplexity, ChatGPT, Raycast, etc.)
• Session Lifecycle Management: Full session state management with pause, resume, end, switch, and delete operations
• Multi-Path Sessions: Sessions can span multiple related directories (monorepos, frontend/backend, etc.)
• Project Isolation: Automatically filters sessions by project path - only see sessions from your current repository
• Auto-Resume: If an active session exists for your project, automatically resume it instead of creating duplicates
• Session Management: Organize work by sessions with automatic channel detection from git branches
• Checkpoints: Create named snapshots of session state with optional git status capture
• Checkpoint Search: Lightweight keyword search across all checkpoints with project/session filtering to find historical decisions
• Smart Compaction: Analyze priority items and generate restoration summaries when approaching context limits
• Channel System: Automatically derive channels from git branches (e.g., feature/auth → feature-auth)
• Local Storage: SQLite database with WAL mode for fast, reliable persistence
• Cross-Tool Compatible: Works with any MCP-compatible client (Claude Code, Cursor, Factory, Codex, Cline, etc.)
• Fully Offline: No cloud account required, all data stays on your machine
• Plans System: Create PRDs and specs, link issues to plans, track implementation progress
• Dashboard UI: Local Next.js web interface for visual session, context, and issue management

📦 Installation

Prerequisites

Bun is required - SaveContext uses bun:sqlite for optimal performance:

# Install Bun (macOS, Linux, WSL)
curl -fsSL https://bun.sh/install | bash

Using bunx (Recommended)

bunx @savecontext/mcp

Global Install

bun install -g @savecontext/mcp

From source (Development)

git clone https://github.com/greenfieldlabs-inc/savecontext.git
cd savecontext/server
bun install
bun run build

⚡️ Quick Start

Get started with SaveContext in under a minute:

# 1. Install Bun (if not already installed)
curl -fsSL https://bun.sh/install | bash

# 2. Add to your AI tool's MCP config

Add this to your MCP configuration (Claude Code, Cursor, etc.):

{
  "mcpServers": {
    "savecontext": {
      "command": "bunx",
      "args": ["@savecontext/mcp"]
    }
  }
}

That's it! Your AI assistant now has persistent memory across sessions.

{
  "mcpServers": {
    "savecontext": {
      "command": "/Users/YOUR_USERNAME/.bun/bin/bunx",
      "args": ["@savecontext/mcp"],
      "env": {
        "PATH": "/Users/YOUR_USERNAME/.bun/bin:/usr/local/bin:/opt/homebrew/bin:/usr/bin:/bin"
      }
    }
  }
}