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Decision brief
Memvid is a Rust-based serverless memory layer that offers instant retrieval and long-term capabilities for AI agents, focusing on simplicity and efficiency.
Good fit when
- When you need a lightweight yet efficient memory solution integrated into your Rust-based AI agents that can manage both short-term and long-term information without requiring complex setup or multi-f
Avoid when
- If you're working with another programming language besides Rust, as Memvid is solely based on Rust and might not integrate seamlessly with other languages.
- In environments where RAG (Retrieval-Augmented Generation) pipelines are already deeply integrated and optimized, as switching to Memvid might require additional refactoring and could potentially be a
- Requirements:
- Requires Rust version 1.85.0 or higher.
Observed Jul 11, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Steady (34d since push)
- As of 1d
- Provenance
- Not a fork · Organization account
- As of 1d
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
cargo add memvidHow it fits your stack(7)
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Evidence and technical details
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Overview
A serverless, single-file memory layer that provides instant retrieval and long-term memory capabilities for AI agents.
Capability facts
- Languages
- rust
Source: github.language · Aug 18, 2026
Categories
Tags
README
Requirements
- Rust 1.85.0+ — Install from rustup.rs
Quick Start
use memvid_core::{Memvid, PutOptions, SearchRequest};
fn main() -> memvid_core::Result<()> {
// Create a new memory file
let mut mem = Memvid::create("knowledge.mv2")?;
// Add documents with metadata
let opts = PutOptions::builder()
.title("Meeting Notes")
.uri("mv2://meetings/2024-01-15")
.tag("project", "alpha")
.build();
mem.put_bytes_with_options(b"Q4 planning discussion...", opts)?;
mem.commit()?;
// Search
let response = mem.search(SearchRequest {
query: "planning".into(),
top_k: 10,
snippet_chars: 200,
..Default::default()
})?;
for hit in response.hits {
println!("{}: {}", hit.title.unwrap_or_default(), hit.text);
}
Ok(())
}
Quick Start: BGE-small (Recommended)
Download the default BGE-small model (384 dimensions, fast and efficient):
mkdir -p ~/.cache/memvid/text-models
---
## License
Apache License 2.0 — see the [LICENSE](LICENSE) file for details.
For agents
This page has a .md twin and JSON over the API.