Lossless, project-scoped memory for AI tools

StackMemory is a memory runtime for AI coding and writing tools that preserves full project context across:

• chat thread resets
• model switching
• editor restarts
• long-running repos with thousands of interactions

Instead of a linear chat log, StackMemory organizes memory as a call stack of scoped work (frames), allowing context to unwind without lossy compaction.

Memory is storage. Context is a compiled view.

Modern AI tools forget:

• why decisions were made
• which constraints still apply
• what changed earlier in the repo
• what tools already ran and why

StackMemory fixes this by:

• storing everything losslessly (events, tool calls, decisions) with infinite remote retention
• using LLM-driven retrieval to inject only the most relevant context
• organizing memory as a call stack with up to 10,000 frames instead of linear chat logs
• providing configurable importance scoring to prioritize what matters for your workflow
• enabling team collaboration through shared and individual frame stacks

Frames can span:

• multiple chat turns
• multiple tool calls
• multiple sessions

• Cloud-backed memory runtime
• Fast indexing + retrieval
• Durable storage
• Per-project pricing
• Works out-of-the-box

• SQLite-based
• Fully inspectable
• Offline / air-gapped
• Intentionally N versions behind
• No sync, no org features

OSS is for trust and inspection. Hosted is for scale, performance, and teams.

StackMemory integrates as an MCP tool and is invoked on every interaction in:

• Claude Code
• compatible editors
• future MCP-enabled tools

The editor never manages memory directly; it asks StackMemory for the context bundle.

stackmemory projects create \
  --repo https://github.com/org/repo

This creates a project-scoped memory space tied to the repo.

npm install -g @stackmemoryai/stackmemory@latest

# Automatic setup - configures MCP and session hooks
npm run claude:setup

This automatically:

• Creates ~/.claude/stackmemory-mcp.json MCP configuration
• Sets up session initialization hooks
• Updates ~/.claude/config.json with StackMemory integration

Manual setup alternative:

mkdir -p ~/.claude
cat > ~/.claude/stackmemory-mcp.json << 'EOF'
{
  "mcpServers": {
    "stackmemory": {
      "command": "stackmemory",
      "args": ["mcp-server"],
      "env": { "NODE_ENV": "production" }
    }
  }
}
EOF

{
  "mcp": {
    "configFiles": ["~/.claude/stackmemory-mcp.json"]
  }
}

Claude Code sessions automatically capture tool calls, maintain context across sessions, and sync with Linear when configured.

Available MCP tools in Claude Code:

git clone https://github.com/stackmemory/stackmemory
cd stackmemory

cargo run --bin stackmemory-mcp
# or
npm run dev

This creates:

.memory/
  └── memory.db   # SQLite

All project memory lives locally.

{
  "tools": {
    "stackmemory": {
      "command": "stackmemory-mcp",
      "args": ["--local"]
    }
  }
}

Each interaction: ingests events → updates indices → retrieves relevant context → returns sized bundle.

{
  "hot_stack": [
    { "frame": "Debug auth redirect", "constraints": [...] }
  ],
  "anchors": [
    { "type": "DECISION", "text": "Use SameSite=Lax cookies" }
  ],
  "relevant_digests": [
    { "frame": "Initial auth refactor", "summary": "..." }
  ],
  "pointers": [
    "s3://logs/auth-test-0421"
  ]
}

• 1 project
• Up to X MB stored
• Up to Y MB retrieval egress / month

• Per-project pricing
• Higher storage + retrieval
• Team sharing
• Org controls

No seat-based pricing.

StackMemory can automatically save context when using Claude Code, so your AI assistant has access to previous context and decisions.

# Add alias
echo 'alias claude="~/Dev/stackmemory/scripts/claude-code-wrapper.sh"' >> ~/.zshrc
source ~/.zshrc

# Use: claude (saves context on exit)

# 1. Shell wrapper (recommended)
claude [--auto-sync] [--sync-interval=10]

# 2. Linear auto-sync daemon
./scripts/linear-auto-sync.sh start [interval]

# 3. Background daemon
./scripts/stackmemory-daemon.sh [interval] &

# 4. Git hooks
./scripts/setup-git-hooks.sh

Features: Auto-save on exit, Linear sync, runs only in StackMemory projects, configurable sync intervals.

Guarantees: Lossless storage, project isolation, survives session/model switches, inspectable local mirror.

Non-goals: Chat UI, vector DB replacement, tool runtime, prompt framework.

# Core
stackmemory init                          # Initialize project
stackmemory status                        # Current status
stackmemory progress                      # Recent activity

# Tasks
stackmemory tasks list [--status pending] # List tasks
stackmemory task add "title" --priority high
stackmemory task done <id>

# Search & Logs
stackmemory search "query" [--tasks|--context]
stackmemory log [--follow] [--type task]

# Context
stackmemory context show [--verbose]
stackmemory context push "name" --type task
stackmemory context add decision "text"
stackmemory context pop [--all]

# Linear Integration
stackmemory linear setup                  # OAuth setup
stackmemory linear sync [--direction from_linear]
stackmemory linear auto-sync --start
stackmemory linear update ENG-123 --status done

# Analytics & Server
stackmemory analytics [--view|--port 3000]
stackmemory mcp-server [--port 3001]

• Hosted: Private beta
• OSS mirror: Early preview
• MCP integration: Stable
• CLI: v0.3.1 - Full task, context, and Linear management

Phase 2 (Current): Query language, LLM retrieval, hybrid digests, scoring profiles
Phase 3: Team collaboration, shared stacks, frame handoff
Phase 4: Two-tier storage, enterprise features, cost optimization

• Hosted service: Proprietary
• Open-source mirror: Apache 2.0 / MIT (TBD)

• ML System Insights - Analysis of 300+ production ML systems
• Agent Instructions - Specific guidance for AI agents working with ML systems

• Product Requirements - Detailed product specifications
• Technical Architecture - System design and database schemas
• Beads Integration - Git-native memory patterns from Beads ecosystem