Savecontext

SaveContext gives AI coding agents the operational layer they're missing — sessions, issue tracking, time tracking, plans, semantic search, and multi-agent coordination, all stored locally in SQLite and available through a native CLI (`sc`) or any MCP-compatible client.

No cloud account. No API keys. No rate limits.

cargo install savecontext-cli && sc init

Quick Start

# Start a session
sc session start "building auth system"

# Save context as you work
sc save auth-choice "JWT with refresh tokens" -c decision -p high
sc save login-done "Login endpoint complete with rate limiting" -c progress

# Track work with issues
sc issue create "Add auth middleware" -t task -p 3
sc issue create "Fix token refresh bug" -t bug -p 4
sc issue claim SC-a1b2

# Check current state
sc status

To connect an MCP-compatible client (Claude Code, Cursor, Codex, Gemini, etc.):

bunx @savecontext/mcp

Then add it to your client's MCP configuration — see [Configuration](#configuration).

Why SaveContext?

The Problem

AI coding agents lose all context between conversations.