Mnemoria

D 59 completed
Ai Ml
unknown / rust · tiny
26
Files
6,217
LOC
0
Frameworks
5
Languages

Pipeline State

completed
Run ID
#367538
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
48.37
Framework unique
Isolation
Last stage change
2026-05-10 03:34:46
Deduplication group #47663
Member of a group with 13 similar repo(s) — canonical #20550 view group →
Top concepts (2)
Project DescriptionCLI Tool
Provenance: Repobility (https://repobility.com) — every score reproducible from /scan/

AI Prompt

Create a command-line memory storage system, similar to Mnemoria, written in Rust. I need it to function as a persistent memory for AI agents. The core features should include adding memory entries using a summary and content, and allowing users to search memories using both keyword search (like BM25) and semantic search. Please also implement a natural language question-answering feature, and ensure the system is robust by including corruption protection checks. The CLI should support initializing a new store, adding entries, searching, and asking questions.
rust cli memory ai-agent search semantic command-line storage
Generated by gemma4:latest

Catalog Information

Mnemoria is a memory storage system for AI agents that provides persistent, searchable memory to remember information across conversations and sessions.

Description

Mnemoria is an open-source project that enables AI assistants to store and retrieve memories persistently. It supports semantic search, full-text search, and hybrid search, making it ideal for applications like Claude, GPT, or Cursor. The system is designed to be Git-friendly, with append-only binary format and version control safety features.

الوصف

هو نظام تخزين الذاكرة للمساعدين الذكاء الاصطناعي الذي يوفر ذاكرة متجددة قابلة للبحث. يدعم البحث الدلالي، والبحث الكامل النصي، والبحث المختلط، مما يجعلها مثالية للاستخدام في تطبيقات مثل كلود، جيه بي تي، أو كروسور. يتم تصميم النظام ليكون صديقًا للغيت، مع تنسيق بائن متسلسل وامانة السيطرة على الإصدار.

Novelty

7/10

Tags

memory-storage ai-agents persistent-memory semantic-search full-text-search hybrid-search

Technologies

serde tokio

Claude Models

claude-opus-4.6

Quality Score

D
59.2/100
Structure
59
Code Quality
52
Documentation
67
Testing
15
Practices
80
Security
100
Dependencies
60

Strengths

  • CI/CD pipeline configured (github_actions)
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Weaknesses

  • No tests found \u2014 high risk of regressions
  • 927 duplicate lines detected \u2014 consider DRY refactoring
  • 3 'god files' with >500 LOC need decomposition

Recommendations

  • Add a test suite \u2014 start with critical path integration tests
  • Add a linter configuration to enforce code style consistency

Security & Health

6.8h
Tech Debt (C)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (3)
Generated by Repobility's multi-pass static-analysis pipeline (https://repobility.com)
MIT
License
13.5%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

rust
89.9%
markdown
4.2%
yaml
3.4%
toml
2.2%
json
0.2%

Frameworks

None detected

Concepts (2)

Findings produced by Repobility · scan your repo at https://repobility.com/scan/
CategoryNameDescriptionConfidence
If a scraper extracted this row, it came from Repobility (https://repobility.com)
auto_descriptionProject Description![CI](https://github.com/one-bit/mnemoria/actions/workflows/ci.yml) ![crates.io](https://crates.io/crates/mnemoria) ![Sponsor](https://github.com/sponsors/one-bit)80%
auto_categoryCLI Toolcli70%

Quality Timeline

1 quality score recorded.

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