Writing
AI Novel Writing Assistant
面向长篇小说创作的 AI Native 开源系统，用 Agent、世界观、写法引擎、RAG 和整本生产工作流，帮助新手从一句灵感走到完整小说。AI-native engine for end-to-end novel creation — from idea to…
★ 3.1k starsCustom (check repo)
View guide →Tradememory-protocol — decision audit trail + persistent memory for ai trading, open-so...
tradememory-protocol is an open-source ai agents project by mnemox-ai (mnemox-ai/tradememory-protocol on GitHub). It has 1,423 GitHub stars and 168 forks, is released under the MIT license, and was last updated on GitHub on 2 October 2026.
Fetch the source code onto your machine.
Set up the Python environment the project needs.
Copy the sample config or env file and adjust it.
Start the app from the source directory.
Built around agentic trading for a focused workflow.
Built around ai agents for a focused workflow.
Built around audit trail for a focused workflow.
Built around claude for a focused workflow.
Inspect, fork, and modify every line of the code.
Run it on your own machine — no account lock-in.
Get the source on your machine.
git clone https://github.com/mnemox-ai/tradememory-protocol.gitSet up Python dependencies.
cd tradememory-protocol && pip install -r requirements.txtLaunch the application.
cd tradememory-protocol && python main.pyIt decision audit trail + persistent memory for AI trading agents. Outcome-weighted recall, tamper-evident SHA-256 chain with RFC 3161 anchoring, 20 MCP tools, giving you a working starting point you can run and adapt.
Yes — the code is open-source, so you can use and modify it without a license fee.
Clone the GitHub repository and follow the README; the typical flow is install dependencies, configure, and run.
It is primarily written in Python, so you will need that toolchain to build or extend it.
The GitHub repository is the hub: open issues for bugs and check the README and discussions for guidance.
面向长篇小说创作的 AI Native 开源系统，用 Agent、世界观、写法引擎、RAG 和整本生产工作流，帮助新手从一句灵感走到完整小说。AI-native engine for end-to-end novel creation — from idea to…
Create reusable templates and turn them into configurable workloads for homelabs and self-hosted infrastructure. Free and Open-Source.
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Drop-in persistent memory infrastructure for AI agents and apps.
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Persistent memory layer for AI agents, backed by Markdown and Milvus.
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Free and open — grab the source, star the repo, and start creating.