User Guide

Everything AIBrain can do — memory, workflows, MCP, mesh networking, evolution, and more.

On this page

  1. Core Concepts
  2. Memory System
  3. CLI Reference
  4. Workflows
  5. Brain Packs
  6. Dashboard
  7. MCP Servers
  8. Multi-Agent Mesh
  9. Self-Learning & Evolution
  10. Marketplace
  11. Tiers & Pricing

Core Concepts

The Brain

A portable SQLite database containing everything your agent knows: memories, skills, workflows, config, and relationship graphs. Copy the file to move your brain to another machine.

Memories

Structured knowledge units with types, importance scores, tags, timestamps, and optional vector embeddings for semantic search.

Workflows

Automated tasks running on schedules or triggers. 55+ built-in scripts covering productivity, research, communication, security, and self-learning.

Brain Packs

Domain specialization bundles. Activate a pack to enable a curated workflow set for a specific use case (developer, content creator, security pro, etc.).

Stacks

The running state of your agent: active workflows, hooks, and services. Save, restore, and share complete configurations.

Mesh

Multi-agent coordination. AIBrain instances sync memories, resolve conflicts by consensus, and distribute merged knowledge to all agents.

Memory System

Storage Architecture

Memory Types

TypePurposeExample
userPreferences, expertise"Senior Go developer, new to React"
feedbackCorrections, validated approaches"Never mock the database in integration tests"
projectOngoing work, goals, deadlines"Merge freeze begins April 5"
referenceExternal resources, locations"Pipeline bugs tracked in Linear"
patternRecurring tendencies"Verify before declaring done"
decisionArchitectural, strategic choices"Chose PostgREST over FastAPI"

Search Modes

AIBrain uses selective query routing — it auto-detects your query type and routes to the best search strategy:

$ aibrain search "kubernetes deployment"     # Search memories
$ aibrain summary                            # Memory stats
$ aibrain brain export                       # Export as JSON
$ aibrain brain import backup.json           # Import from file
$ aibrain forget "outdated topic" --confirm  # Delete memories

CLI Reference

Setup & System

CommandDescription
aibrain setupInteractive first-time setup wizard
aibrain startRestore stack + start services
aibrain statusShow current stack state
aibrain serverStart dashboard at :8001
aibrain mcpStart MCP server (stdio)
aibrain updateSafe self-update (backup, pull, validate)
aibrain versionPrint version

Memory & Brain

CommandDescription
aibrain search <query>Cross-table FTS search
aibrain summaryDashboard statistics
aibrain browseOpen memory browser in web browser
aibrain brain exportExport brain to JSON
aibrain brain import <file>Import from JSON
aibrain brain merge <source>Merge from git URL or local path
aibrain forget <topic>Preview deletion (add --confirm to execute)

Stack & Versioning

CommandDescription
aibrain stack save [name]Save named snapshot
aibrain stack restore [name]Restore from snapshot
aibrain stack rollbackRoll back to previous
aibrain history snapshot <msg>Snapshot current brain state
aibrain history diff <a> [b]Compare versions
aibrain scale compactArchive stale memories

Workflows

AIBrain ships with 55+ workflow scripts organized into categories: Productivity, Research, Communication, Developer, Self-Learning, and System. See the Workflow Reference for the full list.

$ aibrain workflows list                  # Show all workflows + status
$ aibrain workflows enable --recommended  # Enable the starter set
$ aibrain workflows sync                  # Create OS scheduled tasks
$ aibrain workflows run weekly_wins       # Run one immediately

Workflows use your OS scheduler (cron on Linux, schtasks on Windows, launchctl on macOS). No daemon process required.

Brain Packs

PackWorkflowsTier
Productivity8Free
Developer7Pro
Content Creator10Pro
Business7Pro
Security Pro6Pro
Research5Pro
Multi-Agent Ops6Pro
Job Hunter5Pro
$ aibrain packs                       # Browse available packs
$ aibrain packs activate developer     # Activate a pack
$ aibrain packs active                 # Show active packs

Dashboard

Launch with aibrain server. The dashboard runs at http://localhost:8001 and includes 17 pages:

Home

System overview: memory count, active workflows, pending approvals, costs, recent activity.

Memories

Search, browse, create, edit, and delete memories with full-text search.

Memory Graph

Interactive force-directed visualization of knowledge connections.

Workflow Builder

Visual drag-and-drop node editor for creating custom workflows.

Chat

Real-time chat with built-in commands: /status, /approvals, /schedule, /costs.

Approvals

Human-in-the-loop approval queue. Approve or reject pending agent actions.

Costs

Per-model, per-workflow, per-day LLM cost tracking with budget alerts.

API Playground

Postman-style endpoint tester with 17 pre-configured endpoints.

Additional pages: Activity, Settings, Logs, Skills, Backups, Webhooks, MCP Hub, and Integrations.

Keyboard shortcuts: Ctrl+K opens the command palette. ? shows all shortcuts.

MCP Servers

AIBrain ships with 9 MCP servers, making it one of the most comprehensive agent toolkits available. Every server is agent-agnostic — works with Claude, GPT, Cursor, Copilot, Ollama, or any MCP-compatible runtime.

ServerToolsTierDescription
aibrain-memory7FreePersistent memory with selective routing
web-search5FreeZero-config web search
calendar8FreeCalDAV + local .ics management
files10FreeFile search, organize, classify
it-support9ProSystem diagnostics + remediation
peer-discovery15ProMulti-agent mesh + file transfer
design7ProProgrammatic image creation
desktop10ProGUI automation
computer-use1ProFull computer-use via MCP
# Install all MCP servers at once
$ aibrain mcp install

# Or add individually
$ claude mcp add aibrain-memory -- python mcp_server.py --db aibrain.db
$ claude mcp add it-support -- python mcp_it_support.py
$ claude mcp add peer-discovery -- python mcp_peer_discovery.py

Multi-Agent Mesh

Multiple AIBrain instances can coordinate through the agent mesh. Agents register with a broker, exchange messages and files, sync memories, and resolve conflicts through consensus merge.

$ aibrain mesh status                        # Show mesh agent status
$ aibrain mesh register myagent agent.db      # Register an agent
$ aibrain mesh merge                          # Merge all agents (consensus)
$ aibrain mesh distribute                     # Push merged brain to all

Swarm Training

Spin up multiple agent instances, let them learn independently, and harvest the results:

$ aibrain mesh swarm create research -n 100   # Create 100-agent swarm
$ aibrain mesh swarm harvest research          # Merge swarm results

Self-Learning & Evolution

AIBrain agents improve over time through built-in self-learning workflows:

These run silently in the background. You don't interact with them directly — they just make everything better over time.

Marketplace

Package and sell trained brain configurations. Buyers get domain expertise instantly without the training time.

$ aibrain marketplace package --name "devops-brain"  # Package for sale
$ aibrain marketplace publish devops-brain.brain     # Publish
$ aibrain marketplace search "machine learning"      # Browse
$ aibrain marketplace install <id>                   # Install a brain
$ aibrain marketplace revenue                        # Revenue dashboard

Tiers & Pricing

Free Free

Full memory system, CLI, MCP memory server, Productivity brain pack, web search, file management, basic workflows. Everything you need to get started.

Pro $9.95/mo

All brain packs, all 9 MCP servers, multi-agent mesh, marketplace access, swarm training, IT support, design tools, desktop automation, computer-use.

$ aibrain license tiers              # See pricing details
$ aibrain license activate <key>     # Activate your license
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