MCP.so
ログイン

OpenLore MCP Server認証済み注目

@aakarim

基本情報

OpenLore MCP Server について

Serve your docs to AI agents over SSH and MCP. Agents use ls, cat, grep, find, and pipes against a virtual filesystem backed by your documentation. Identity-scoped access, governed writing with human approval, and portab

OpenLore MCP Server の設定

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": {
    "openlore": {
      "command": "openlore",
      "args": [
        "./docs"
      ]
    }
  }
}

OpenLore MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

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 OpenLore?

Serve your docs to AI agents over SSH and MCP. Agents use ls, cat, grep, find, pipes, and shell loops against a virtual filesystem backed by your documentation. No ingestion pipeline, no vector DB. Point it at a directory and it serves the existing hierarchy directly.

How it works

Agent ──SSH or MCP──▶ OpenLore ──▶ docs, knowledge, and artifacts

By default it starts SSH on localhost:2222, a web view on http://localhost:8080, and MCP over HTTP on http://localhost:8080/mcp.

Key features

  • Agent-native retrieval — agents use the shell tools they already know instead of learning a bespoke API
  • One knowledge surface, multiple transports — SSH, SFTP/SSHFS, MCP, and a human-friendly web view
  • Identity-scoped views — each agent sees only the docsets it needs, with role-based access
  • Governed writing — writes are atomic, conflict-aware, and can require human approval
  • Safe by construction — the shell is an in-memory Go interpreter, not a real OS shell. No escape, no arbitrary execution
  • Portable knowledge bundles — embed docs into a self-contained binary or package as a desktop MCP extension

Use cases

  • Internal API docs, runbooks, and architecture notes for coding agents
  • Shared live memory for teams of agents across sessions
  • Agent Skills publishing into governed, discoverable collections
  • Remote review of agent-generated reports and artifacts through SSH or browser

Quick start

go install github.com/aakarim/go-openlore/cmd/openlore@latest
openlore ./docs
ssh -p 2222 localhost

コメント

「メモリとナレッジ」の他のコンテンツ