This release is a pre-release and may not be stable for production use.
HyperClaw
Your personal AI that actually gets things done.
HyperClaw is a personal AI assistant that works across your entire life. Not just chat — it connects to your email, calendar, tasks, documents, and more. It remembers everything, learns your preferences, and coordinates 44 specialized AI agents to help you with anything.
What's New in v0.2.0
- Claude 5 family with tiered model routing (sonnet-5 / opus-5 / fable-5) and automatic failover — overloads degrade gracefully instead of going silent
- Universal file delivery — the
send_filetool pushes any document, deck, spreadsheet, image, or video into the conversation you're already in (Telegram documents, iMessage attachments, email attachments) or opens it on the Mac - Full email suite — HTML email, in-thread replies, forwarding with attachments, drafts-as-approval, archive/star/read, Gmail search
- Offsite heartbeat — a dead-man's-switch template that alerts you externally if
the machine running your assistant dies (see
.env.example→HEARTBEAT_URL) - Persona templating — your assistant's identity lives in an untracked file
(
persona.example.md), not in source code - Hardened channel security — fail-closed allowlists for iMessage and Telegram; see SECURITY.md before exposing the bot to any channel
What Can It Do?
- Manage your communications — Email, Telegram, Slack, Discord, WhatsApp, Teams
- Organize your work — Calendar, tasks, projects, documents
- Handle your data — Notion, Airtable, Google Sheets, Salesforce, HubSpot
- Support your business — Invoicing, customer tracking, sales pipelines
- Research anything — Web search, document analysis, data synthesis
- Remember everything — Your preferences, history, context across all sessions
- Optimize costs — Smart model routing uses cheap models for simple tasks
One AI. Every platform. All working together.
Architecture
Cost-Optimized Model Router
HyperClaw intelligently routes tasks to the most cost-effective model:
| Model | Use Case | Cost (input/output per 1k tokens) |
|---|---|---|
| ChatJimmy (Llama 3.1 8B) | Simple queries, classification, quick lookups | ~$0.00001 |
| Claude Haiku 4.5 | Moderate tasks, basic analysis | $0.001 / $0.005 |
| Claude Sonnet 5 | Everyday requests, drafting, quick answers | $0.002 / $0.010 |
| Claude Opus 5 | Analysis, planning, writing, research | $0.005 / $0.025 |
| Claude Fable 5 | Hardest multi-step work: code, architecture, quant | $0.010 / $0.050 |
Simple "what time is it?" stays cheap. "Refactor this system end to end" gets Fable 5 — and if a model is overloaded, the failover chain walks down the ladder instead of dropping your request.
Multi-Agent Coordination
44 specialized agents organized by domain:
- Business (11): Strategos, Herald, Pipeline, Ledger, Counsel, Talent, Nexus, Ops, Revenue, Sovereign, Venture
- Personal (6): Atlas, Midas, Vitals, Nourish, Navigator, Hearth
- Scientific (5): Medicus, Cosmos, Gaia, Oracle, Scribe
- Communications (5): Echo, Envoy, Pulse, Cipher, Herald
- Talent (4): Scout, Deal, Stage, Roster
- Trading (3): Prediction Strategist, Polymarket Trader, Global Prediction Engine
- Technology (3): Aegis, Bridge, Forge
- Recursive (3): Scout, Alchemist, Calibrator
- Intelligence (2): Sentinel, Arbiter
- Creative (2): Author, Lens
Tasks are automatically routed to the best agent based on domain and complexity.
Persistent Memory
Memory persists across sessions:
- Working Memory — Current context and active tasks
- Episodic Memory — Conversation history and decisions
- Semantic Memory — Facts and knowledge
- Instincts — Learned behavioral patterns
Getting Started
Option 1: Quick Start (5 minutes)
macOS:
brew install pipx
pipx install hyperagents # the command is still `hyperclaw`
hyperclaw init
Linux/Windows:
pip install hyperagents
hyperclaw init
The init command runs an interactive setup that will:
- Ask for your name and what to call your AI
- Guide you through API key setup (Anthropic)
- Optionally set up database for persistent memory
- Launch the chat interface
Then use interactive chat:
hyperclaw start
Or run the TUI:
hyperclaw-tui
Option 2: Self-Host with Docker
# Clone the repo
git clone https://gitlab.com/hyper-nimbus-group/hyperclaw.git
cd hyperclaw
# Copy the example config
cp .env.example .env
# Edit .env and add your Anthropic API key
# ANTHROPIC_API_KEY=sk-ant-your-key
# Optional: Add ChatJimmy for cheap simple tasks
# CHATJIMMY_API_KEY=your-taalas-key
# Start
docker-compose up
Open http://localhost:8001 in your browser.
Option 3: Production Setup
# Clone and setup
git clone https://gitlab.com/hyper-nimbus-group/hyperclaw.git
cd hyperclaw
pip install -r requirements.txt
# Initialize workspace and config
python -m hyperclaw setup
# Initialize database (requires DATABASE_URL in .env)
python -m hyperclaw setup --init-db
# Start server
python -m hyperclaw server --port 8001
Configuration
Required
- ANTHROPIC_API_KEY — Powers the AI brain
- Get one at console.anthropic.com
Recommended
-
DATABASE_URL — PostgreSQL with pgvector for memory
- Easiest: Supabase (free tier works)
- Run
schema/init.sqlto create tables
-
CHATJIMMY_API_KEY — Cheap model for simple tasks
- Get one at taalas.ai
- Reduces costs by 90%+ for simple queries
Optional Integrations
Messaging:
TELEGRAM_BOT_TOKEN=your-bot-token
SLACK_BOT_TOKEN=xoxb-your-token
Telegram polling and the scheduled jobs (heartbeat, morning brief, nightly
memory consolidation) are off by default. They start only with
HYPERCLAW_UNATTENDED=1; see docs/UNATTENDED-MODE.md.
Email:
GMAIL_CLIENT_ID=...
GMAIL_CLIENT_SECRET=...
GMAIL_REFRESH_TOKEN=...
See .env.example for all available integrations.
API Endpoints
Chat
# Simple chat
curl -X POST http://localhost:8001/chat \
-H "Content-Type: application/json" \
-d '{"message": "What can you help me with?"}'
# Streaming chat
curl -X POST http://localhost:8001/chat/stream \
-H "Content-Type: application/json" \
-d '{"message": "Explain quantum computing", "stream": true}'
Tasks
# Create a task
curl -X POST http://localhost:8001/api/tasks \
-H "Content-Type: application/json" \
-d '{"goal": "Research competitors in AI space", "domain": "business"}'
# Get task status
curl http://localhost:8001/api/tasks/abc123
# List all tasks
curl http://localhost:8001/api/tasks
Multi-Agent Coordination
# Coordinate complex goal across multiple agents
curl -X POST http://localhost:8001/api/coordinate \
-H "Content-Type: application/json" \
-d '{"goal": "Create a complete marketing strategy for product launch"}'
Memory
# Store a memory
curl -X POST http://localhost:8001/api/memory/remember \
-H "Content-Type: application/json" \
-d '{"content": "User prefers concise responses", "importance": 0.8}'
# Recall memories
curl -X POST http://localhost:8001/api/memory/recall \
-H "Content-Type: application/json" \
-d '{"query": "user preferences"}'
Cost Management
# Get current costs
curl http://localhost:8001/api/costs
# Set daily budget
curl -X POST "http://localhost:8001/api/costs/budget?budget_usd=5.0"
# List available models
curl http://localhost:8001/api/models
System
# Health check
curl http://localhost:8001/health
# Full status
curl http://localhost:8001/status
# List agents
curl http://localhost:8001/api/agents
# List integrations
curl http://localhost:8001/api/integrations
CLI Commands
# Setup workspace and configuration
hyperclaw setup
hyperclaw setup --init-db # Also initialize database
# Start the server
hyperclaw server
hyperclaw server --port 8080
# Interactive chat
hyperclaw chat
# Check status
hyperclaw status
# Memory operations
hyperclaw memory list
hyperclaw memory recall "user preferences"
hyperclaw memory remember "Important note"
# Version
hyperclaw version
Workspace Structure
After setup, HyperClaw creates:
~/.hyperclaw/
├── workspace/
│ ├── SOUL.md # AI personality
│ ├── IDENTITY.md # AI configuration
│ ├── USER.md # Your profile
│ ├── MEMORY.md # Working memory
│ └── secrets/
│ └── .env # API keys
├── memory/
│ ├── instincts.md # Learned behaviors
│ ├── core-episodes.md # Key memories
│ └── daily/ # Daily logs
├── config/
│ └── hyperclaw.yaml # System config
└── logs/
Edit these files to customize your assistant's behavior.
Cost Optimization Tips
-
Use ChatJimmy — Add
CHATJIMMY_API_KEYto route simple tasks to a model that costs 100x less -
Cost caps — every model call goes through the cost guard (
hyperclaw/cost_guard.py). At the daily cap or the per-task cap HyperClaw stops (no further model calls, never a cheaper model) and asks you whether to continue, with what was done (from the activity log and tool results), what remains and the spend so far. Answers above a small amount end with a spend line. Scheduled jobs and guest chats stop and notify you only.hyperclaw costshows today's spend;hyperclaw cost raise --daily 20/--task 5(or/cost raise daily 20in the terminal) changes a cap — your explicit action, recorded inhyperclaw activity.- Settings:
config.jsonkeycost_guard(daily_cap_usd, default 10;task_cap_usd, default 2;spend_line_min_usd, default 0.01;prices), else the environment (HYPERCLAW_DAILY_CAP_USD— legacyDAILY_BUDGET_USD—HYPERCLAW_TASK_CAP_USD,HYPERCLAW_SPEND_LINE_MIN_USD). Hyper deployments set them inconfig.json. - Prices are USD per 1k tokens:
cost_guard.prices({"<model>" or "provider:<name>": {"input_per_1k": …, "output_per_1k": …}}), thenmodels.yamlcost_per_1k_*, then a built-in table. HyperSpeed V2 uses a placeholder rate until Hyper sets its internal rate asprices["provider:hyperspeed"]. An unknown model is charged a conservative rate, never 0. Spend is kept per day in$HYPERCLAW_ROOT/ledger/cost.sqlite3(survives restarts).
-
Enable prefer_cheap — Set
PREFER_CHEAP_MODELS=trueto always prefer the cheapest capable model -
Monitor usage — Check
/api/coststo see spend by model
Database Setup (Optional but Recommended)
For persistent memory across sessions, set up PostgreSQL with pgvector:
- Create a Supabase project (free) or use any PostgreSQL
- Enable the
vectorextension - Run
schema/init.sqlto create tables - Add
DATABASE_URLto your.env
# Initialize database
python -m hyperclaw setup --init-db
Privacy & Security
- Your data stays yours — Self-host means nothing leaves your machine
- No tracking — We don't collect anything
- Open source — Audit the code yourself
- Per-agent permissions — Control what each agent can access
- Channel allowlists — iMessage/Telegram deny strangers by default; read SECURITY.md before connecting any channel
Troubleshooting
For terminal authentication errors after a Hyperspeed outage, see provider recovery.
"API key not working"
- Make sure it starts with
sk-ant- - Check for extra spaces when pasting
"Database connection failed"
- Verify your DATABASE_URL is correct
- For Supabase, use the "Transaction pooler" connection string
"Integration not connecting"
- Run
hyperclaw integrations test <name>to diagnose - Check that API keys are in your
.envfile
Need help?
- Run
hyperclaw statusto check system health - Open an issue on GitLab
Contributing
MIT licensed. Contributions welcome.
git clone https://gitlab.com/hyper-nimbus-group/hyperclaw.git
cd hyperclaw
pip install -e ".[dev]"
python -m pytest tests/ -v
See CONTRIBUTING.md for guidelines.
License
MIT — use it, modify it, build on it.
Metadata
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