How is Projectmem different from a simple memory store?
It is not just a memory store—it is a judgment layer that surfaces past failures at the exact moment you would repeat the mistake.
@riponcm
基本信息
Local-first memory and judgment layer for AI coding agents. Captures issues, failed attempts, fixes, and decisions in readable Markdown + JSONL, re-injects them into future sessions, and warns at git commit before you repeat a mistake. 14 tools, works with Claude, Cursor, Antigra
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"projectmem": {
"command": "pjm-mcp",
"args": [
"--root",
"/absolute/path/to/your/project"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Projectmem is a local-first memory and judgment layer for AI coding agents. It captures development history—issues, failed attempts, fixes, decisions, and gotchas—into readable Markdown + JSONL inside your repository, and feeds that context back to your AI agent through the Model Context Protocol (MCP).
Install with pip install projectmem, then configure your MCP client with command: "pjm-mcp" and args: ["--root", "/absolute/path/to/your/project"]. The server exposes 14 MCP tools that your AI client can use to read and write project memory directly.
git commit before repeating a known mistakeIt is not just a memory store—it is a judgment layer that surfaces past failures at the exact moment you would repeat the mistake.
Projectmem requires Python (installed via pip) and a local directory for storage. It is open source (MIT license).
All data is stored locally inside your repository as plain‑text Markdown and JSONL files, so you can `git diff` them.
It uses standard I/O (stdio) via the Model Context Protocol.
No. Projectmem is 100% local; there is no cloud component or telemetry.
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