Memvid

Memvid is an AI platform that provides a single-file memory layer and instant retrieval for agents.

Memvid is a knowledge layer and memory system designed for AI agents and enterprise search. It stores data, embeddings, indices, and a write-ahead log in a single portable file. Users can import documents, notes, and conversations, which the system automatically chunks, embeds, and indexes. Developers connect any AI model or agent through MCP, the SDK, or a direct API to get hybrid recall and persistent memory. The platform features sub-5ms hybrid search combining BM25 lexical matching with semantic vector embeddings, entity extraction, and time-travel debugging. It runs locally, on-premise, or in private and public clouds without requiring traditional databases or servers.

Memvid at a glance

Best for: Software engineer
Runs on: Web, API, self-hosted
Pricing: Free
Released: May 2025
Category: AI agent tool
Website: memvid.com

Key features

Single-file architecture using portable memory files
Sub-5ms hybrid search combining BM25 and semantic vectors
Automated document chunking, embedding, and indexing
Entity extraction for structured data processing
Time-based queries with a built-in timeline index
Crash-safe design with an embedded write-ahead log
Multiple connection options including MCP, SDK, and API

Use it for

Powering long-term memory for AI agents
Running enterprise search over company knowledge
Automating workflows with instant document recall
Handling time-sensitive conversational history

Alternatives to Memvid

memsearch — It shares continuous context across Claude Code, Codex, and other AI coding agents.
memU — It gives every connected agent a shared and inspectable memory layer.
Mem0 — It provides drop-in persistent memory for AI agents without changing pipelines.
Supermemory — Integrates long-term memory into AI coding agents with a single prompt.
MemPalace — Achieves high recall with local-first storage and zero API calls.
ReMe — It enables local-first, file-native long-term memory sharing across multiple AI agents.
SimpleMem — Provides semantic lossless compression to reduce token consumption and maintain long-term context.
claude-mem — It shares persistent, searchable agent memory across sessions and devices.
Agentmemoryrepo — Enables agents to navigate memories like a wiki and share knowledge across sessions.
AgentMemory — It runs locally with zero external databases and achieves high retrieval recall.
M-Flow — It achieves a 93.7 percent top-one hit rate using a conical memory architecture.
Memori — Reduces LLM token usage and spend by over 97% with targeted recall.

All Memvid alternatives