What does Mimirs do that alternatives do not?
Mimirs combines vector search with BM25, AST-aware chunking for 24 languages, dependency graph boosting, conversation memory, checkpoints, annotations, and wiki generation in a single local-first tool.
@TheWinci
基本信息
Persistent project memory for AI coding agents. Hybrid vector + BM25 search with AST-aware chunking (24 languages), dependency graph boosting, conversation memory, checkpoints, annotations, and wiki generation. Local-first, zero config. `bunx mimirs init`
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mimirs": {
"command": "bunx",
"args": [
"mimirs@latest",
"serve"
],
"env": {
"RAG_PROJECT_DIR": "path/to/your/folder"
}
}
}
}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。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
Mimirs is a persistent project memory system for AI coding agents. It provides hybrid vector and BM25 search with AST-aware chunking for 24 programming languages, dependency graph boosting, conversation memory, checkpoints, annotations, and wiki generation. It is local-first and requires zero configuration.
Initialize a Mimirs project by running bunx mimirs init in your project directory.
Mimirs combines vector search with BM25, AST-aware chunking for 24 languages, dependency graph boosting, conversation memory, checkpoints, annotations, and wiki generation in a single local-first tool.
Mimirs requires only `bun` (to run `bunx mimirs init`) and runs locally with no external services.
All data is stored locally on the user’s machine; Mimirs is local-first.
The README does not specify transport or authentication mechanisms.
The README does not list any known limitations.
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