SHIPLAB MCP

Carrier Cost Data for AI

Connect Claude, OpenAI Codex, and supported MCP workflows to the carrier data available across your Shiplab organization—through one maintained connection.
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SEE HOW IT WORKS
CARRIER DATA FOR AI

AI cannot work with carrier data it cannot reach.

Carrier cost data is fragmented across portals, APIs, SFTP, email delivery, PDFs, CSVs, and carrier-specific formats.

Before AI can explore, analyze, or build with that data, someone has to collect it, maintain every connection, and preserve the underlying detail.

Shiplab handles that layer – continuously collecting carrier-native invoice, shipment, and charge-level data and making it accessible through MCP, API, cloud storage, and managed delivery.

EXPLORE CONNECTORS

One-off input

A temporary snapshot

FedEx_June.csv
UPS_Invoice.pdf
charges.xlsx
AI prompt Limited to uploaded files

Export, upload, ask—and repeat when the data changes.

Shiplab MCP

Connected carrier context

Carriers
Accounts
Invoices
Shipments
Charges
History
AI workflow Current data context
Continuously available
CARRIER DATA IN CONTEXT

Give AI more than a carrier data snapshot.

A single invoice, CSV, or carrier export can answer a narrow question. It cannot give AI the broader context across your carriers, accounts, invoices, shipments, and charges.

Shiplab continuously collects detailed carrier-native data into one accessible layer. Through Shiplab MCP, supported AI tools can work with the current records available across your organization—without beginning every question with another export or upload.

Connect once. Query the carrier data already flowing through Shiplab

GET STARTED
Move from finding the data to working with it.

Ask the data. Literally.

Once your carrier records are accessible to AI, teams can explore available data, investigate changes, generate code, and build workflows without beginning with manual exports or another carrier integration project.

EXPLORE CONNECTORS

EXPLORE

AI WORKSPACE
SHIPLAB MCP CONNECTED
S
What would you like to explore across your connected carriers?
Compare weekly billed charges and shipment counts across UPS and FedEx for the last 12 weeks.

Flag the largest changes and show the invoice and shipment records supporting each finding.
Ask about your carrier data… ↑

INVESTIGATE

AI WORKSPACE
SHIPLAB MCP CONNECTED
S
What should I investigate in your available carrier data?
Within each carrier, find the charge types that changed most over the last eight weeks.

Summarize the differences by carrier and account, then list the underlying charge records for review.
Ask about your carrier data… ↑

BUILD

AI WORKSPACE
SHIPLAB MCP CONNECTED
S
What would you like to build with your Shiplab data?
Create a Python workflow that retrieves newly available invoice records from Shiplab.

Load the available shipment- and charge-level data and prepare it for our internal reporting model.
Ask about your carrier data… ↑
HOW IT WORKS

From carrier source to AI context.

Shiplab MCP builds on the carrier collection infrastructure already operating beneath the Shiplab platform.
1
Connect Your Carriers

Add and manage your carrier connections through the Shiplab management portal or API.

2
Shiplab Collects

Shiplab continuously collects available carrier data and maintains the source-specific workflows as portals, APIs, files, formats, and delivery methods change.

3
Add Shiplab MCP

Connect Shiplab MCP to Claude, OpenAI Codex, or another supported MCP client.

4
Ask, Build, and Automate

Use your AI environment to retrieve available records, explore carrier data, generate code, and build workflows around your requirements.

1. Connecting carriers
2. Collecting carrier data
3. Shiplab MCP connected
4. Building the workflow
U
UPS account Credentials connected
F
FedEx account Credentials connected
R
Regional carrier Credentials connected
Invoices
Shipments
Charges
Source files
SHIPLAB MCP
C
Claude MCP client
</>
Codex MCP client
Find newly available invoices and prepare the related records for our internal workflow.
✓
Carrier-data workflow prepared Current records retrieved through Shiplab MCP

Carrier-Native Context

Use the invoice, shipment, charge-level, and source-file detail available to your organization.

Maintained Infrastructure

Shiplab maintains the underlying portals, APIs, credentials, files, formats, and carrier-source changes.

Vendor-Neutral Access

Use MCP alongside API, S3, data-lake, and managed file delivery without tying your data to one AI tool.

Your AI tools may change. Your carrier data layer does not have to.

COMMON QUESTIONS

Shiplab MCP, explained.

Shiplab MCP builds on the carrier collection infrastructure already operating beneath the Shiplab platform.

The exact tools and records available depend on your Shiplab organization, carrier connections, and the current MCP release.

This may include organization and carrier context, invoice records, source files, and available shipment- and charge-level data.

Shiplab is initially supporting and documenting Claude and OpenAI Codex.

Support may expand as additional MCP-compatible clients are tested and validated.

The Shiplab API is designed for direct programmatic integration into applications, products, and data systems.

MCP is designed to let supported AI tools and agents discover and use available Shiplab data and capabilities through prompts and agentic workflows.

They are complementary access methods.

No. Shiplab provides the carrier-data infrastructure and access layer.

The AI tool, application, or workflow you connect determines how the data is analyzed, summarized, visualized, or used.

Yes. Shiplab MCP works with carrier connections and data managed through your Shiplab organization.

No. MCP is an additional access method.

You can continue using Shiplab’s API, cloud storage, data lake, S3, or managed file-delivery workflows alongside MCP.

Shiplab MCP

Bring your carrier data into the AI tools your team already uses.

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