OpenAI builds and deploys advanced AI models like GPT-4o for autonomous agents and workflows.
Clawputer
$0.01Starting price
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About Clawputer
Clawputer is a managed OpenClaw AI agent that runs continuously inside an OpenComputer sandbox. It routes user queries to Claude through OpenRouter and integrates with gbrain, a Postgres-backed persistent memory system featuring vector search and an MCP/plugin SDK. The tool exposes a Telegram bot interface with hot-reload configuration, enabling developers to deploy and customize a persistent automation or assistant with minimal setup. Users can access their always-on AI assistant directly from a phone, while the system retains context and knowledge across interactions. The setup requires only three commands and eliminates the need for manual server management. Developers can extend functionality using plugins or the MCP protocol, making it suitable for both personal and professional automation tasks. The combination of continuous operation, persistent memory, and conversational interfaces creates a seamless experience for users who need reliable, long-running AI assistance.
Key features
- Continuous operation in an OpenComputer sandbox
- Persistent memory with Postgres-backed storage and vector search
- Integration with Claude via OpenRouter for query routing
- Telegram bot interface with hot-reload configuration
- MCP/plugin SDK for extensibility
- Three-command deployment process
- No manual server management required
- Phone-accessible always-on AI assistant
- Context retention across interactions
- Knowledge indexing and retrieval
Use cases
- Deploying a persistent personal AI assistant accessible via phone
- Building custom automation workflows with persistent memory
- Creating long-running AI agents for customer support or internal tools
Pros
- Always-on Linux sandbox with persistent memory via gbrain (Postgres + vector search)
- Native integration with iMessage or Telegram for seamless access without additional apps
- Supports 3,000+ app integrations and tools like browser automation, terminal commands, and MCP servers
- No manual server management required; setup involves only three commands
- Durable sessions that can hibernate, resume, or be steered mid-run
Cons
- Limited to iMessage or Telegram interfaces; no native web or desktop app
- Early access pricing may change after the introductory period
- Requires familiarity with TypeScript or OpenComputer CLI for custom agent development
- Persistent memory and continuous operation may incur higher usage costs over time
Frequently asked questions about Clawputer
What is Clawputer and what does it do?
Clawputer is a personal AI assistant that runs continuously inside a Linux sandbox with persistent memory. It processes user queries via iMessage or Telegram, performs tasks like scheduling, automation, and research, and retains context across interactions.
Who is Clawputer suitable for?
Clawputer is designed for developers, professionals, and power users who need an always-on AI assistant for automation, research, or task management. It is particularly useful for those comfortable with iMessage or Telegram.
How does the pricing model work?
Clawputer operates on a pay-as-you-go model with prepaid usage credits. Model calls are billed at API rates, and machine time is charged per second. Plans offer prepaid credits with multipliers, and users can bring their own model subscriptions.
Can I extend Clawputer’s functionality?
Yes, Clawputer supports plugins and the MCP protocol, allowing users to add custom tools, MCP servers, or integrations. Developers can write agents in TypeScript and deploy them with the OpenComputer CLI.
What are the setup requirements for Clawputer?
Setting up Clawputer requires installing the OpenComputer CLI, signing in, and deploying an agent. No additional apps or signup forms are needed, and the process can be completed in minutes.
Does Clawputer retain memory between sessions?
Yes, Clawputer uses gbrain, a Postgres-backed persistent memory system with vector search, to retain context and knowledge across interactions. This allows the assistant to remember past tasks and preferences.
