DevRag - Lightweight Local RAG MCP Server

Name: DevRag - Lightweight Local RAG MCP Server
Author: tomohiro-owada

@tomohiro-owada

リポジトリ

DevRag - Lightweight Local RAG MCP Server について

Lightweight local RAG MCP server for semantic vector

#devrag #local-server #semantic-search

基本情報

カテゴリ

メモリとナレッジ

トランスポート

stdio

公開者

tomohiro-owada

投稿者

Owada Tomohiro

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "devrag": {
      "type": "stdio",
      "command": "/usr/local/bin/devrag"
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is DevRag - Lightweight Local RAG MCP Server?

DevRag is a lightweight, local-only MCP server that provides Retrieval-Augmented Generation (RAG) capabilities to MCP hosts (e.g., Claude Desktop). It performs semantic vector search over indexed markdown files, dramatically reducing token usage and search latency—all without any API dependencies or costs.

How to use DevRag - Lightweight Local RAG MCP Server?

DevRag is distributed as a single binary with no dependencies. To use it, launch the binary and configure your MCP host to point to it. Once running, the server exposes tools such as search, index_markdown, list_documents, delete_document, and reindex_document for managing and querying your local knowledge base.

Key features of DevRag - Lightweight Local RAG MCP Server

40x token reduction via semantic vector search
15x faster responses (~95ms search latency)
Runs entirely locally – no API costs
Multi-language support – Japanese and English
Filtered search by directory and filename patterns
Single binary with no external dependencies

Use cases of DevRag - Lightweight Local RAG MCP Server

Augmenting an AI assistant with a local markdown knowledge base
Indexing personal documentation or project wikis for fast retrieval
Reducing token usage in RAG pipelines when using paid LLM APIs
Multi-language RAG for teams working in Japanese and English

FAQ from DevRag - Lightweight Local RAG MCP Server

Is DevRag truly local and free?

Yes. It runs entirely on your machine, with no API calls or external services, so there are no usage costs.

What are the runtime requirements?

DevRag ships as a single binary with no dependencies—just download and execute.

Which languages does it support?

Indexing and search are available in both Japanese and English.

How do I add my documents?

Use the index_markdown tool to add a markdown file to the index, and list_documents to review indexed content.

What transport does it use?

The server follows the Model Context Protocol, which typically uses STDIO transport for host–server communication.

Are there any limits on document size or number?

The README does not specify explicit limits; performance and index capacity depend on the local environment.

「メモリとナレッジ」の他のコンテンツ

Zettelkasten MCP Server

entanglr

A Model Context Protocol (MCP) server that implements the Zettelkasten knowledge management methodology, allowing you to create, link, explore and synthesize atomic notes through Claude and other MCP-compatible clients.

159