mnemon-dev/mnemon
LLM-supervised persistent memory for AI agents — graph-based recall, cross-session knowledge, single binary. Works with DeepSeek Harness, Claude Code, OpenClaw, and any agent runtime.
⚡ Executive Summary & Quick Facts
Authoritative Sourcemnemon is mnemon is an open-source project written in Go: LLM-supervised persistent memory for AI agents — graph-based recall, cross-session knowledge, single binary. Works with DeepSeek Harness, Claude Code, OpenClaw, and any agent runtime..
| Repository | mnemon-dev/mnemon ↗ |
|---|---|
| Primary Category | agent framework |
| Language & Stack | Go |
| Software License | Apache-2.0 |
| Community Traction | ★ 638 stars · ⑂ 75 forks · #8,041 globally |
| Maintenance | ● Active (Last commit: Oct 18, 2026) · 12 open issues |
| Target Audience | Developers and engineering teams building with Go, seeking reliable, tested, and actively maintained tooling for production workloads. |
Star History
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+16
STARS · LAST 30 DAYS
1
PER DAY
#912
MOST-STARRED Go
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +7 | +16 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +1 | +3 | +10 |
mnemon gained 16 stars in the last 30 days, about 1 a day, and now has 638. It is about 1 year old and has averaged roughly 638 stars a year. It ranks #912 among Go repositories and #8,041 across all languages on GitHubRepo.
Trending Record
1
DAYS ON TRENDING
#9086
BEST RANK
Oct 19, 2026
FIRST APPEARANCE
Active
STATUS TODAY
mnemon has maintained a continuous presence across global trending indexes, peaking at #9086. Below is the 30-day activity profile:
💡 Overview
mnemon is an open-source project written in Go: LLM-supervised persistent memory for AI agents — graph-based recall, cross-session knowledge, single binary. Works with DeepSeek Harness, Claude Code, OpenClaw, and any agent runtime.
Engineered for speed, consistency, and developer ease, it solves common hurdles in agent-framework, agent-memory, ai-agent. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Go for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ go install github.com/mnemon-dev/mnemon@latest⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Go >= 1.21 runtime environment
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
mnemon coordinates its core functionality through a modular Go pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with mnemon.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install mnemon using your package manager: `go install github.com/mnemon-dev/mnemon@latest`
Initialize your project workspace or configuration file for mnemon.
Import mnemon into your codebase or invoke it directly from your terminal.
Execute your test suite or run `mnemon --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Go, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
mnemon-dev/mnemon is currently ranked #8,041 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #8,036 | hector-client/hector | Java | ★ 639 | Compare ↗ |
| #8,036 | scalecube/scalecube-services | Java | ★ 639 | Compare ↗ |
| #8,036 | 5e-bits/5e-srd-api | TypeScript | ★ 639 | Compare ↗ |
| #8,036 | OmniSharp/csharp-language-server-protocol | C# | ★ 639 | Compare ↗ |
| #8,036 | vassalengine/vassal | Java | ★ 639 | Compare ↗ |
| #8,041 | mnemon-dev/mnemon This Project | Go | ★ 638 | |
| #8,041 | JakeWharton/flip-tables | Java | ★ 638 | Compare ↗ |
| #8,041 | kuvasz-uptime/kuvasz | Kotlin | ★ 638 | Compare ↗ |
| #8,041 | aelassas/bookcars | TypeScript | ★ 638 | Compare ↗ |
| #8,041 | AIDotNet/NextCoWork | TypeScript | ★ 638 | Compare ↗ |
| #8,041 | narumiruna/pi-extensions | TypeScript | ★ 638 | Compare ↗ |
Frequently Asked Questions
What does mnemon do? +
LLM-supervised persistent memory for AI agents — graph-based recall, cross-session knowledge, single binary. Works with DeepSeek Harness, Claude Code, OpenClaw, and any agent runtime.
What language is mnemon written in? +
The primary language is Go. Topics include: agent-framework, agent-memory, ai-agent, ai-tools, claude.
Is mnemon actively maintained? +
Yes, the last recorded push was on Oct 18, 2026 with 12 open issues being tracked.
How many stars does mnemon have? +
mnemon has 638 stars and 75 forks on GitHub.
How does mnemon rank among GitHub repositories? +
With 638 stars, mnemon-dev/mnemon is ranked #8,041 globally across all repositories tracked on GitHubRepo and #912 among Go projects.
What license is mnemon distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
