sachinsharma9780/memweave — Memweave is a zero-infrastructure, async-first Python library that gives AI agents persistent, searc…

Description and use

Memweave is an async‑first, zero‑infrastructure Python library that equips AI agents with persistent, searchable memory by storing data as plain Markdown files. It lets developers add long‑term context to agents without setting up databases or external services, and provides simple APIs for adding, retrieving, and querying the stored notes. Ideal for orchestration, AI/ML workflows, and DevOps pipelines where lightweight, file‑based knowledge bases are preferred.

Problem

sachinsharma9780/memweave helps turn isolated prompts and tools into repeatable agent workflows.

Outcome

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

Workflow

• coordinate multi-agent workflows
• add tool-use pipelines
• standardize agent memory

Evidence

memweave is a zero-infrastructure, async-first Python library that gives AI agents persistent, searchable memory — stored as plain Markdown files

Source