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Atlas – Ai Transport Logistics Agent Standard

Atlas – Ai Transport Logistics Agent Standard

Local
github.com/cargofyAI & Agents20Updated 34w ago

About Atlas – Ai Transport Logistics Agent Standard

ATLAS 是面向物流企业的开源 MCP 服务,可在企业安全边界内连接业务系统并索引运营数据。它让 AI Agent 查询运输、承运商、费率和路线等上下文,同时支持本地 AI 运行。

Key features

  1. 01本地索引物流运营数据
  2. 02查询运输、承运商、费率和路线
  3. 03连接 REST API 与本地文件
  4. 04提供物流数据 Web 界面
  5. 05支持文档实体提取与知识扩充
  6. 06令牌权限控制与审计日志

Use cases

  1. 01查询货运状态并回应客户
  2. 02基于历史运输数据比较承运商
  3. 03结合费率和路线信息进行采购分析
  4. 04在本地整理并检索物流文件

MCP support

ATLAS 通过 MCP 暴露物流数据发现、查询、货运、承运商、费率和运营问题等工具,供兼容的 Agent 调用。

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"ATLAS": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"cargofy/atlas:latest"
]
}
}
}
Run commanddocker run -i --rm cargofy/atlas:latest

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
ocicargofy/atlas:latest

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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.

License: Apache 2.0 MCP Compatible Docker


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 -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

Web UI

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

PageDescription
DashboardServer status, record counts, connector health, SLA violations
ExplorerBrowse data models, execute queries with visual filters
ChatConversational AI interface with tool calling for logistics queries
PlaygroundTest MCP tools directly from the browser
Knowledge BaseManage enterprise knowledge files (markdown, folders, CRUD)
ImportUpload data files (JSON, CSV, XLSX), seed database, import from folders
ConnectorsView and manage data source configurations, trigger manual sync
ModulesEnable/disable plugins, trigger sync, view module status
SettingsVisual + YAML config editor with live reload
Setup WizardFirst-run configuration (AI provider, security, instance name)

MCP Tools

ATLAS exposes 35 MCP tools via the Model Context Protocol. Any MCP-compatible agent can connect:

CategoryTools
Discoveryget_available_models, get_schema, get_available_carriers, get_available_lanes, get_available_document_types, get_sync_status
Queryget_records, query (natural language search across all data)
Shipmentsget_shipment, get_shipments, get_shipment_events, get_unsigned_documents, get_closure_checklist
Carrierssearch_carriers, get_carrier_shipments
Ratesget_rate_history
Documentslist_documents
Operationsget_sla_violations, get_idle_assets, get_anomalies, get_active_issues (20+ disruption types)

AI Features

ATLAS supports multiple AI providers with role-based model routing:

ProviderModelsUse
AnthropicClaude Sonnet/Opus/HaikuChat, extraction, knowledge enrichment
OpenAIGPT-4o, GPT-4o-miniChat, extraction
OllamaAny local modelFully offline operation

AI capabilities:

  • Entity extraction — upload any logistics document (PDF, CSV, XLSX, email) and extract structured data (shipments, carriers, rates, documents)
  • Knowledge enrichment — AI automatically updates your knowledge base from extracted data, detecting contradictions and appending new facts
  • Chat with tools — conversational interface that queries your data using MCP tools
  • Role routing — assign different models to different tasks (chat, extraction, knowledge)

Data Models

Core Models (always enabled)
ModelDescription
ShipmentsOcean, air, road, rail, multimodal — status, mode, route, carrier, planned delivery
CarriersProfiles, type (trucking, shipping line, airline, rail, broker), country, rating
LanesOrigin → destination pairs with mode and average transit days
RatesFreight pricing by carrier, lane, mode, date range
DocumentsBOL, CMR, AWB, invoice, customs, POD, packing list, certificate of origin
Tracking EventsPickup, transit, delivery, exception events with location and geolocation
Service LevelsPlanned transit times per lane/mode/service type
Extension Models (opt-in via config)

Assets, Drivers, Transport Orders, Facilities, Tenders, Tender Quotes, Tender Awards, Dispatches, Legs, Customs Entries


Connectors

ConnectorStatusDescription
REST APIAvailableGeneric REST with JSONPath mapping, bearer/basic/api_key auth
FilesystemAvailableLocal JSON, CSV, TXT, MD files (optional PDF/DOCX/XLSX)
AI ExtractAvailableUpload files for AI-powered entity extraction
Email (IMAP/Exchange)v0.2Indexes logistics-related emails
SAP TMComing soonSAP Transportation Management
Oracle TMSComing soonOracle Transportation Management
TransporeonComing soonTransporeon platform integration
project44Coming soonVisibility and tracking data

Modules (Plugins)

ModuleDescription
file-watchMonitor a local folder for new files, auto-process through AI extraction pipeline
knowledge-enricherAutomatically enrich knowledge base from AI extractions
google-driveSync files from Google Drive folders with AI analysis (Docs/Sheets export, recursion)

Modules are enabled/disabled via config.yml or the Modules page in Web UI.


Architecture

ATLAS Instance (your infrastructure)
├── AI Layer
│   ├── Multi-provider LLM client (Claude, OpenAI, Ollama)
│   ├── Entity extraction pipeline
│   ├── Knowledge engine (enrichment + contradiction detection)
│   └── Chat with tool calling
├── Module System (plugin architecture)
│   ├── file-watch
│   ├── knowledge-enricher
│   └── google-drive
├── Connectors
│   ├── REST API connector
│   ├── Filesystem connector
│   └── AI extraction connector
├── Storage Layer
│   ├── SQLite (default) or PostgreSQL
│   └── Knowledge base (markdown files)
├── MCP Server
│   ├── stdio transport (CLI / Claude Desktop)
│   └── HTTP/SSE transport (remote agents)
└── Web UI + REST API
    ├── Dashboard, Explorer, Chat, Playground
    ├── Knowledge Base manager
    ├── Settings, Modules, Import
    └── Setup Wizard

Security & Privacy

  • Zero data egress — ATLAS never sends your raw data outside your network
  • Local AI option — run Ollama for fully offline operation
  • Bearer token auth — scoped permissions (read/write) per token
  • Non-root Docker — runs as unprivileged atlas user
  • Audit logs — full log of every query made to your instance
  • Open source — inspect every line of code

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.


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:

punkpeye/awesome-mcp-servers appcypher/awesome-mcp-servers wong2/awesome-mcp-servers modelcontextprotocol/servers PulseMCP MCP Index Cursor Directory

Submit, discover, and explore MCP servers in the ecosystem.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.