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serverlessclaw

agent
SUMMARY

Official ServerlessClaw: The authoritative autonomous AI agent swarm for AWS. /opt/homebrew/bin/bash idle cost, self-evolving, and infinite scale. Powered by OpenClaw.

README.md

Serverless Claw - Autonomous AI Agent Swarm for AWS

Serverless Claw - Autonomous AI Agent Swarm for AWS Infrastructure

SST v3 AWS Lambda DynamoDB EventBridge Next.js TypeScript Vitest Playwright Self-Evolution License MIT

The Self-Evolving AI Agent Swarm for AWS
$0 when idle. Elastic by design. Secure by default.
Autonomous infrastructure management • AI-powered code evolution • Serverless-first architecture

🌐 Website • 🚀 Get Started • 📖 Blog • 💬 Discord

💎 The 3 Pillars of Serverless Claw

🚀 Infinite Scale 🧠 Self-Evolution 🛡️ Cloud-Native Safety
$0 when idle. Lambda scales to zero. No VPS, no Docker daemon, no 24/7 server costs. Council-Verified. Agents write code, run tests, and redeploy the stack via a peer-reviewed loop. Zero Trust. No SSH keys, no persistent daemons. IAM least-privilege and DMS rollback.

Why Serverless for AI Agents?

In 2026, the 24/7 VPS mascot is dead. Running AI agent swarms on persistent pods is an expensive relic of the container era.

Serverless Claw is an open-source autonomous agent framework that:

  • 💰 Cost Efficient: You pay exactly for the tokens and compute you use. A complex reasoning task might cost $0.05; staying idle costs $0.
  • ⚡ Instantly Elastic: Need 1,000 agents to research a topic in parallel? Serverless Claw fans out across AWS Lambda instantly.
  • 🔧 Maintenance Free: No Docker security patches, no OS updates, no resource exhaustion. Just pure intelligence.
  • 🔒 Secure by Default: IAM least-privilege, no SSH keys, no persistent daemons.
  • 📈 Auto-Scaling: Scales from 0 to thousands of agents based on demand.

Use Cases:

  • Autonomous code review and improvement
  • Infrastructure monitoring and auto-remediation
  • Research and data analysis at scale
  • DevOps automation and CI/CD optimization
  • Cost optimization for AWS resources

Council-Verified Evolution

Serverless Claw doesn't just execute code; it improves itself. But unlike raw autonomous systems, every evolution is gated by a Council of Agents.

  [ Cognition Reflector ] ───▶ [ Strategic Planner ]
                                        │
                                        ▼
  [ Coder Agent ] ◀─────── [ Council of Agents ] (Safety Gate)
        │
        ▼
  [ Deployer (CodeBuild) ] ──▶ [ Build Monitor ] ──▶ [ QA Auditor ] ──▶ [ DONE ]

How It Works

You (Messenger)        SuperClaw (Lambda)       AgentBus (EB)       Specialized Agents (x8)
      │                       │                      │                       │
      └─▶ "Feature X" ────────▶ [THINK: Strategic] ──▶ DISPATCH_TASK ────────▶ [EXECUTE]
                              │                      │                       │
      ◀─▶ Real-time Dashboard ◀─ [ASYNC: Pause] ◀──── [BUS ROUTING] ◀────────┤
                              │                                              │
      ◀─────────────────────── [IOT CORE / MQTT] ◀── [SIGNAL_ORCH] ◀─────────┘

When you send a message, SuperClaw receives it, develops a plan with the Strategic Planner, and dispatches tasks to specialized nodes via EventBridge. The system implements an Asynchronous "Pause & Resume" pattern — agents don't block; they emit a task and terminate, waking up only when a result signal is routed back. High-impact plans are peer-reviewed by the Council of Agents, while the Facilitator moderates collaborative sessions to drive consensus.

🤖 The Multi-Agent Ecosystem

Agent Responsibilities
SuperClaw Orchestrator. Interprets intent, delegates tasks, and deploys.
Strategic Planner Designs long-term evolution and expansion plans.
Coder Agent Writes code, fixes bugs, and performs migrations.
QA Auditor Verifies the technical satisfaction of every deployment.
Facilitator Moderates collaboration between multiple agents and humans.
Cognition Reflector Distills memory and identifies system-wide gaps.
Critic Agents Peer-reviewers for Security, Performance, and Architecture.

⚡️ Quick Start (AWS-Native)

Deploy your first autonomous swarm in 5 minutes.

1. Zero-Install Deploy

git clone https://github.com/serverlessclaw/serverlessclaw.git
cd serverlessclaw && pnpm install

2. Secure Your Keys

cp .env.example .env
# Essential: SST_SECRET_OpenAIApiKey & SST_SECRET_TelegramBotToken

3. Launch Local Dev

make dev # Live lambda reloading, local DynamoDB, and real-time logs

4. Deploy to AWS

make deploy ENV=dev # High-availability, production-grade infrastructure

📚 Documentation

Document Description
INDEX.md Start here - Documentation hub and context map
ARCHITECTURE.md System topology and AI-native principles
docs/AGENTS.md Agent roster and evolutionary loop
docs/MEMORY.md Tiered memory engine
docs/TOOLS.md Tool registry and MCP standards
docs/SAFETY.md Circuit breakers and rollback safety
docs/DEVOPS.md DevOps and CI/CD
docs/ROADMAP.md Future plans

🌐 Managed Service (ClawMore)

For a fully managed experience with auto-scaling, monitoring, and support, check out ClawMore - the premium managed version of ServerlessClaw.

ClawMore Features:

  • One-click deployment
  • Automatic infrastructure management
  • AI-powered code evolution
  • Real-time monitoring dashboard
  • Priority support

🆚 The 2026 "Claw" Comparison

Feature OpenClaw NanoClaw ZeroClaw Serverless Claw (Us)
Infrastructure
Architecture Monolithic Node.js Micro TypeScript Native Rust Binary Event-Driven Serverless (Lambda)
Operational Cost High (24/7 Server) Moderate (VPS/Docker) Low (Raspberry Pi) Zero Idle Cost ($0 when not in use)
Scalability Manual Cluster Docker Swarm Hardware-bound Elastic Auto-scale (AWS Native)
Agent Runtime
Multi-Agent Basic "Fire & Forget" Containerized Swarms Trait-based Modular Non-blocking (Pause & Resume)
Self-Evolution Plugin-based (Static) Manual (Human-coded) Hardware-focused Verified Council-Reviewed Loop
Communication Mode Natural Language Structured (JSON) Low-level Buffers Dual-Mode (Intent-Based JSON + Text)
Skill Acquisition Static (Hardcoded) Static (Hardcoded) Static (Config-based) Just-in-Time (JIT) Skill Discovery
Tooling & Integration
Tooling Architecture Static Registry Static (JSON) Static (Hardcoded) Hub-First Dynamic Discovery
MCP Integration Not Supported Local Stdio Only Low-level C FFI SSE/Stdio Hybrid (Hub-First)
Vision Capability OCR / Text-only Basic Base64 Edge Inference S3-mediated Multi-modal Pipeline
Memory
Memory Model SQLite / Local File Volatile Cache Flash Storage Tiered Memory Engine + Hit Tracking
Collaborative Memory None (Log-based) Minimal (JSON) None ClawCenter Neural Reserve Hub
Reliability & Ops
Observability Standard Text Logs Container Logs Binary Logs Trace Graphs (ClawTracer)
Resilience Manual Recovery Restart Container Hardware Watchdog Autonomous Heartbeat + Rollback
Resource Safety App-level Permissions Sandboxing (Docker) Memory Safe (Rust) Cloud IAM + Multi-Agent Council

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Ways to contribute:

  • ⭐ Star the repository
  • 🐛 Report bugs via GitHub Issues
  • 💡 Suggest new features
  • 🔧 Submit pull requests
  • 📖 Improve documentation

📄 License

MIT License - see LICENSE for details.

🌐 clawmore.ai • 📧 [email protected] • 💬 Discord Community

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