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.

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.

Quick Start

Option 1: Docker (recommended)

docker run -d \
  -v ./config.yml:/app/config.yml \
  -v atlas_data:/data/atlas \
  cargofy/atlas:latest

Option 2: Claude Desktop

Add to your claude_desktop_config.json under mcpServers:

{
  "atlas": {
    "command": "docker",
    "args": ["run", "--rm", "-i", "-v", "/your/data:/data", "cargofy/atlas:latest"]
  }
}

Option 3: Run from source

git clone https://github.com/cargofy/ATLAS
cd ATLAS
npm install
node seed.js          # optional: load sample data
node src/index.js     # starts MCP server on stdio

Configure your data sources in config.yml (copy from config.example.yml).

Connectors

| Connector | Status | Description | |-----------|--------|-------------| | Email (IMAP/Exchange) | 🔜 v0.2 | Indexes all logistics-related emails | | Filesystem (JSON, CSV, PDF) | ✅ Available | Local contracts, BOLs, rate sheets | | REST API | ✅ Available | Connect any TMS or ERP via API | | SAP TM | 🔜 Coming soon | Native SAP Transportation Management | | Oracle TMS | 🔜 Coming soon | Oracle Transportation Management | | Transporeon | 🔜 Coming soon | Transporeon platform integration | | project44 | 🔜 Coming soon | Visibility and tracking data |

Data Models

ATLAS ships with logistics-native data models covering all transport modes:

Shipment — ocean, air, road, rail, multimodal
Carrier — profiles, performance history, rates
Route — lanes, corridors, transit times
Document — BOL, CMR, AWB, customs declarations
Rate — historical pricing, spot vs contract
Event — pickup, transit, delivery, exception

These models are the foundation. Agents query against them — not raw data.

MCP Interface

ATLAS exposes a standard Model Context Protocol server. Any MCP-compatible agent can connect:

# Any AI agent connecting to ATLAS
client = MCPClient("http://atlas.yourcompany.internal:3000")

# Ask for context — data never leaves your perimeter
context = client.query("best carrier for Warsaw–Hamburg lane, last 6 months")
# → Returns structured insights from your own data

Architecture

ATLAS Instance (your infrastructure)
├── Ingestion Layer
│   ├── Email connector
│   ├── Document connector
│   └── TMS/ERP connectors
├── Processing Layer
│   ├── Logistics entity extraction
│   ├── Vector embeddings (local)
│   └── Structured data models
├── Storage Layer
│   ├── Vector store (local)
│   └── Relational index (SQLite/PostgreSQL)
└── MCP Server
    ├── Query interface
    ├── Context retrieval
    └── Agent authentication

Use Cases

Carrier Negotiation Agent

Agent queries ATLAS: "What's our volume with DHL on DE→PL in Q4?" → Gets answer from your own data → Negotiates from a position of knowledge.

Customer Service Agent

"Where is shipment #12345?" → Agent queries ATLAS for shipment status from your TMS → Answers instantly without manual lookup.

Procurement Agent

"Who are the top 3 carriers for refrigerated transport to Ukraine?" → Agent pulls from your historical performance data in ATLAS → Makes data-driven recommendation.

Security & Privacy

Zero data egress — ATLAS never sends your raw data outside your network
Local embeddings — all vector processing happens on your infrastructure
Agent authentication — control which agents can query your ATLAS instance
Audit logs — full log of every query made to your instance
Open source — inspect every line of code

Powered by Cargofy

ATLAS is built and maintained by Cargofy — the AI platform for logistics. We built ATLAS because our enterprise customers needed it. We open-sourced it because the logistics industry needs a standard.

Cargofy platform connects to your ATLAS instance to provide:

AI agents that make calls, send messages, negotiate on your behalf
Analytics and reporting on top of your ATLAS data
Managed ATLAS hosting (if you prefer not to self-host)
Enterprise connectors and SLA support

→ Learn more about Cargofy

Contributing

ATLAS is Apache 2.0 licensed. Contributions welcome.

git clone https://github.com/cargofy/atlas
cd atlas
npm install
npm run dev

See CONTRIBUTING.md for guidelines.

License

Apache License 2.0 — see LICENSE

Listed In

ATLAS is submitted to the following MCP directories and lists:

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