Pieces Long-Term Memory (MCP)v1.0.3

An AI agent handles customer inquiries while storing conversation history and resolved issues in Pieces LTM. The agent can recall past interactions across sessions, enabling personalized and consistent support without manual logging.

A user runs PiecesOS on a desktop and connects via a mobile agent using this skill. The agent stores personal notes, project ideas, and research snippets, retrieving them later for planning or writing tasks.

An agent collects web research, creates memories in Pieces, and later retrieves them for blog or report writing. The long-term memory allows the agent to build knowledge over time and produce coherent, informed content.

Operations agents log incidents, root causes, and solutions as pieces memories. When similar issues recur, the agent queries Pieces LTM to suggest proven fixes, reducing resolution time and promoting institutional knowledge.

A sales agent stores lead interactions, preferences, and deal stages in Pieces LTM. It retrieves context on each contact to personalize follow-ups, send timely reminders, and maintain a complete sales history.

Offer Pieces LTM as a premium add-on for AI agent platforms, charging a monthly fee per user or agent for persistent, cross-session memory. Revenue comes from recurring subscriptions, with upsells for advanced search and larger storage.

License Pieces LTM integration to enterprises that deploy custom AI agents internally. Charge per-seat or per-agent plus a base fee for dedicated tunnel infrastructure and support. Revenue includes installation, training, and ongoing maintenance contracts.

Monetize each Pieces MCP call (e.g., ask_pieces_ltm or full_text_search) for high-volume use cases. Provide a free tier for light usage, then charge per 1,000 queries or per MB of data ingested and retrieved.