Build portable single-file agent memory with Memvid
Use Memvid when an agent needs local, portable long-term memory and retrieval without running a vector database or full RAG service.
npx skills add agentskillexchange/skills --skill build-portable-single-file-agent-memory-with-memvid
npm install @memvid/sdk, the CLI with npm install -g memvid-cli, the Python SDK with pip install memvid-sdk, or the Rust crate with cargo add memvid-core.Memvid packages documents, embeddings, search indexes, and metadata into portable `.mv2` memory files that agents can carry between sessions or environments.
What this skill actually does
Use this skill when an operator needs to ingest a bounded document or project corpus, create a single-file memory capsule, query it locally for relevant context, and hand retrieved snippets back to an agent workflow. The boundary is portable memory creation and retrieval for agents; it is not a general vector database listing, a hosted RAG product card, or a broad SDK reference.
Typical workflow: install the Memvid CLI or SDK, create a memory file, add documents with metadata, commit the capsule, run semantic or lexical search, and attach the retrieved context to the next agent task. This is most useful for offline-first agents, auditable project memory, handoff bundles, or environments where running separate retrieval infrastructure is too heavy.
Source evidence: upstream describes Memvid as a single-file memory layer for AI agents with instant retrieval, long-term memory, append-only Smart Frames, capsule context, time-travel debugging, SDKs, and CLI support.