A project author reports building an open-source, unattended Xiaohongshu pipeline that uses a cron-scheduled Hermes Agent to search for AI news, verify source dates, write five-point summaries, render two 1080×1440 cards, publish through browser automation, and confirm public visibility. Because the author says Xiaohongshu has no open publishing API or MCP server, the system uses the Chrome DevTools Protocol to control a persistent Edge instance, with nine Python scripts handling deterministic steps. The author reports that the system ran from September 14 to November 2, 2026, producing 35 publications, three failed task runs, 15 no-run days because the local gateway was down, and no duplicate publications; these figures were not independently verified.
What problem it solves
Personal AI agents need to connect language model providers, communication channels, and tools while remaining under the user's control. They also need configurable autonomy, security boundaries, and operational features such as background services, approvals, and persistent workflows.
Key features
Multiple channels and providers — The agent can receive messages through conf…
What problem it solves
Managing multiple coding agents across separate terminals leaves users responsible for scheduling, checking, and merging their work. Teams also need a practical way to route tasks across models, automate recurring work, and operate the same development process in interactive or headless environments.
Key features
One workspace for every project — A single interface lists pro…
What problem it solves
Agentic workloads often need durable state, live client connections, scheduling, and fault-tolerant execution. Rivet addresses these needs with long-lived Actors that can represent individual agents, users, sessions, tenants, workflows, or applications.
Key features
Stateful Actors — Each Actor combines a long-lived process with in-memory state, durable SQLite storage, WebSo…
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