ScottRBK/forgetful — Opensource Memory for Agents

Description and use

ScottRBK/forgetful is an open‑source library that provides a lightweight, differentiable memory module designed for AI agents, enabling them to store, retrieve, and selectively forget information during training and inference. By integrating a controllable forgetting mechanism, the project helps improve long‑term reasoning and reduces memory bloat in reinforcement learning and language model applications. It is released under an MIT license and can be easily plugged into existing PyTorch‑based pipelines.

Problem

ScottRBK/forgetful helps connect AI assistants to real tools and data through a standard protocol.

Outcome

Early or unclear: treat as research material until maintenance, releases, docs, and issue activity are verified.

Workflow

• connect AI agents to tools
• ship Model Context Protocol servers
• standardize integrations

Evidence

Opensource Memory for Agents

Source