Memveri Agent Operating System

Memveri vs the field

Memveri isn't another coding agent. It's the memory, code-intelligence, and safety layer that works on top of the agent you already use. Here's how the pieces compare, fact by fact.

Memveri — Agent OS layer Claude Code — Anthropic's agent OpenCode — open-source CLI agent MiMo Code — ByteDance coding agent
Capability
Memveri
Claude Code
OpenCode
MiMo Code
Cross-session memorysurvives restarts, searchable
Yes — semantic vector memory
Partial — markdown context files
No — stateless sessions
Partial — SQLite FTS5 files
Memory recall rankingrelevance scoring, not just full-text
Yes — embeddings + decay scoring
No
No
No — FTS5 keyword search
Code knowledge graphfunctions, classes, calls, imports
Yes — 2,658 nodes / 96 files on Memveri 1.3.1
No
No
No
Guardrail decision ledgeraccept / reject / supersede, auditable
Yes — rules engine + ledger
Partial — permission rules & hooks
Partial — permissions config
Partial — permissions config
Works with any agentMCP server for external tools
Yes — 77 tools, 9 core (1.3.1 minimal)
No — Claude only
Partial — consumes MCP
Partial — consumes MCP
Team / multi-machine syncshare memory across machines
Yes — export/import bundles
No — machine-local files
No
No — machine-local files
Local-first datano cloud required
Yes — SQLite on your disk
Partial — local files, cloud login
Yes
Yes
Open sourcesource you can inspect and fork
Yes
No — proprietary
Yes — MIT
Yes — MIT

Measured on our own codebase — 1.3.1 scale on D:\

Real numbers from tests/test_scale_benchmarks.py on D:\ (Windows 11, 1.3.1 ponytail build, MEMVERI_BACKUP=0, Hash provider). Voyage lifts recall further (see below). Synthetic micro-benches kept for reference.

Indexing throughput

10 files0.19s
50 files1.03s
100 files2.51s
200 files5.70s

Synthetic tree, full build.

Scale verified — D:\ 1.3.1

50k memories

Insert 50k (skip_fts→sync)116s (431/s)
100 recalls on 10k63s (1.6 q/s)
Consolidate 1k dupes10.08s
1.3.1 vectorized

Threshold <180s for 50k, vectorized normed@normed.T vs O(N²) loop. D: free 354GB.

Real repo — 1.3.1

Memveri itself96 files
Graph nodes2,658
Graph edges5,043
Communities48

Full build 40.9s (was 38.7s) — single COUNT + single SELECT for communities; 100× get_neighbors 0.0s (cache).

Recall accuracy — voyage lifts

Hash (fallback)50% (2/4)
Voyage-code-2 (auto)100% (4/4)
Cohere rerank opt-in+5–10% NDCG

4-query bench (auth/db topics). VOYAGE_API_KEY auto-picks voyage; COHERE_API_KEY reranks limit*2 after RRF.

The other tools are excellent agents. None of them give you a persistent, tool-agnostic memory with a guardrail ledger and a code knowledge graph.

Add Memveri on top of the one you already use — and keep it.

Download for Windows
How we scored this comparison

Feature matrix reflects public documentation as of July 2026. "Partial" means the capability exists in a limited form — e.g. Claude Code's memory is guidance loaded into context, not an enforced, searchable store (per Anthropic's own docs), and MiMo Code's memory is SQLite full-text search, not semantic recall.