开源MCP服务器，为AI代理提供关于您的物流运营的深入上下文——而您的数据从未离开您的基础设施。

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问题

企业物流公司拥有多年的运营数据——电子邮件、合同、TMS记录、承运商关系、定价历史。AI代理需要这些背景才能发挥作用。但与外部云服务共享原始数据对合规、法律和安全团队来说是不可行的。

结果是：人工智能依然浅薄。代理无法从上下文中谈判。每一次互动都从零开始。

解决方案

ATLAS运行在你的安全边界内。它连接你现有系统，本地索引你的数据，并暴露标准化的MCP接口。任何AI代理都可以查询ATLAS——获取深度运营上下文——而你的数据从未离开你的基础设施。

你的数据会留在你身边。客服人员获得所需的背景信息。

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快速启动

选项1：Docker（推荐）

打开http://localhost:3000——设置向导将引导你完成初始配置。

关于带有持久数据和AI功能的生产应用，请参见 DOCKER.md。

选项2：Claude桌面版

ATLAS — AI Transport Logistics Agent Standard

The open-source MCP server that gives AI agents deep context about your logistics operations — without your data ever leaving your infrastructure.

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The Problem

Enterprise logistics companies have years of operational data — emails, contracts, TMS records, carrier relationships, pricing history. AI agents need this context to be useful. But sharing raw data with external cloud services is a non-starter for compliance, legal, and security teams.

The result: AI stays shallow. Agents can’t negotiate from context. Every interaction starts from zero.

The Solution

ATLAS runs inside your security perimeter. It connects to your existing systems, indexes your data locally, and exposes a standardized MCP interface. Any AI agent can query ATLAS — getting deep operational context — without your data ever leaving your infrastructure.

[Your Company]                        [Cargofy / Any AI Agent]
  ├── Email                                      │
  ├── TMS                    MCP Protocol        │
  ├── ERP          ←─────────────────────────────┤
  ├── Contracts              (questions only,    │
  ├── Knowledge Base          no raw data out)   │
  └── ATLAS instance ────────────────────────────┘

Your data stays with you. Agents get the context they need.

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Quick Start

Option 1: Docker (recommended)

docker run -p 3000:3000 cargofy/atlas

Open http://localhost:3000 — the Setup Wizard will guide you through initial configuration.

For production use with persistent data and AI features, see DOCKER.md.

Option 2: Claude Desktop

Add to your claude_desktop_config.json under mcpServers:

{
  "atlas": {
    "command": "docker",
    "args": ["run", "--rm", "-i", "cargofy/atlas", "node", "src/index.js"]
  }
}

Option 3: Run from source

git clone https://github.com/cargofy/ATLAS
cd ATLAS
npm install
cp config.example.yml config.yml   # edit with your settings
node seed.js                       # optional: load sample data
node src/ui-server.js              # Web UI + API on port 3000
# or
node src/index.js                  # MCP server on stdio

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Web UI

ATLAS ships with a full web interface at http://localhost:3000: