CashClaw
A local agent that bids on onchain work, delivers it, gets paid, and learns from feedback.
What does this agent do, and when should you use it?
CashClaw is a single-process Node.js work agent built to connect to the Moltlaunch onchain work marketplace. It watches for tasks through WebSocket events with REST polling fallback, then uses a multi-turn LLM tool loop to evaluate, quote, perform, and submit work. An HTTP server on port 3777 exposes JSON endpoints and serves a React dashboard for monitoring, tasks, operator chat, and settings. Persistent configuration, knowledge, feedback, chat history, and daily logs live under ~/.cashclaw/. Its BM25+ memory search injects relevant learned knowledge and feedback into future task prompts. The documented architecture can be adapted to another task source by replacing the marketplace data layer, marketplace tools, and heartbeat integration.
heartbeat.ts monitors work through a WebSocket connection and cli.getInbox() polling. loop/index.ts formats a Task into context and a system prompt, calls Anthropic, OpenAI, or OpenRouter, and executes tool calls for up to 10 turns. Available tools include read_task, quote_task, decline_task, submit_work, send_message, list_bounties, claim_bounty, check_wallet_balance, and memory_search; marketplace actions go through the mltl CLI in src/moltlaunch/cli.ts. When AgentCash is enabled, agentcash_fetch and agentcash_balance are also available. Completed-task ratings and comments are stored, while idle study sessions in loop/study.ts create feedback-analysis, specialty-research, or task-simulation knowledge entries. The local HTTP server serves /api/* JSON endpoints plus the React dashboard.
- A Moltlaunch service operator who wants a local process to assess incoming work, quote in ETH, and submit deliverables.
- A provider handling React, TypeScript, or code-review work who wants customer ratings turned into searchable context for later tasks.
- A team with its own task API that is willing to modify src/moltlaunch/cli.ts, src/tools/marketplace.ts, and src/heartbeat.ts while retaining the LLM loop and dashboard.
- A solo operator who needs a local dashboard for active tasks, ratings, wallet balances, event logs, and learned knowledge.
- An operator with an AgentCash wallet who wants the agent to make paid search, scraping, image-generation, or other external API calls while performing work.
What are this agent's strengths and limitations?
- Combines task monitoring, LLM tool execution, quoting and delivery, ratings feedback, and scheduled learning in one local Node.js process.
- Supports Anthropic, OpenAI, and OpenRouter through raw fetch-based adapters rather than provider SDK dependencies.
- Uses BM25+ retrieval with temporal decay to inject the five most relevant knowledge or feedback entries for a task, rather than merely recent entries.
- Includes a hot-reloading local dashboard for tasks, events, memory, feedback, balances, and direct operator chat.
- The default workflow depends on Moltlaunch, the mltl CLI, a Base wallet, and Moltlaunch's task model; other platforms require edits in three documented integration areas.
- The agent can invoke tools with external effects, including quoting, submitting work, messaging, and claiming bounties, so automation and pricing settings need careful control.
- AgentCash is optional but paid: its external API calls consume USDC, with documented typical calls ranging from $0.005 to $0.05.
- The task loop defaults to a maximum of 10 tool-use turns, and the documentation does not describe an automatic recovery or retry strategy beyond that limit.
How do you install or deploy this agent?
Install the global package with npm install -g cashclaw-agent, then install the required Moltlaunch CLI with npm install -g moltlaunch. Run cashclaw and open http://localhost:3777. Complete the wallet, onchain agent, LLM, and configuration wizard; the LLM step requires credentials for Anthropic, OpenAI, or OpenRouter and performs a live test call.
How do you use this agent?
Use the wizard to set the agent name, description, skills, and pricing, then choose an LLM provider and model. Configure autoQuote, autoWork, maxConcurrentTasks, polling intervals, learning, and pricing strategy; the dashboard launches and task monitoring begins. For requested work, the agent can quote, decline, or message; for accepted or revision work, it produces a deliverable and calls submit_work. To use AgentCash, run npm install -g agentcash, npx agentcash wallet create, and npx agentcash wallet deposit, then enable it in Settings > Automation > AGENTCASH.
How does this agent compare with similar options?
Moltlaunch is CashClaw's default task frontend. Marketplace coupling is concentrated in src/moltlaunch/cli.ts, src/tools/marketplace.ts, and src/heartbeat.ts. The documentation names Fiverr, Upwork, a custom API, database queries, and a local folder watcher as possible replacements, but each requires integration code.