Freightview MCP Server for Mastra AI 12 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Freightview through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.
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Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token. get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"freightview": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Freightview Agent",
instructions:
"You help users interact with Freightview " +
"using 12 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Freightview?"
);
console.log(result.text);
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Freightview MCP Server
Connect your Freightview account to any AI agent to automate your LTL (Less-Than-Truckload) freight quoting and logistics management through the Model Context Protocol (MCP). Freightview is a centralized platform that connects shippers with all their carriers in one place. This MCP server enables you to request real-time rates, monitor active shipments, and oversee your logistics network directly through natural conversation.
Mastra's agent abstraction provides a clean separation between LLM logic and Freightview tool infrastructure. Connect 12 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
Key Features
- Real-time Quoting — Request freight rates from all your connected carriers simultaneously by providing origin and destination details.
- Shipment Tracking — List all active shipments and fetch detailed tracking metadata including current transit status and estimated delivery.
- Carrier Oversight — Access and list all carriers connected to your account to maintain full visibility of your logistics partners.
- Logistics Directory — Access your saved address book and item catalog to facilitate faster and more accurate quoting.
- Webhook Integration — Monitor active webhooks configured for real-time status updates and automated logistics notifications.
- Account Metadata — Fetch detailed account attributes and contact information to maintain full context of your shipping operations.
- Audit & History — Retrieve historical quotes and shipment details for better cost analysis and reporting.
The Freightview MCP Server exposes 12 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Freightview to Mastra AI via MCP
Follow these steps to integrate the Freightview MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 12 tools from Freightview via MCP
Why Use Mastra AI with the Freightview MCP Server
Mastra AI provides unique advantages when paired with Freightview through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Freightview without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every Freightview tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
Freightview + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Freightview MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Freightview, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Freightview as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Freightview on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Freightview tools alongside other MCP servers
Freightview MCP Tools for Mastra AI (12)
These 12 tools become available when you connect Freightview to Mastra AI via MCP:
get_account_details
Get organization attributes
get_carrier_details
Get carrier info
get_quote_details
Get quote metadata
get_shipment_details
Get shipment metadata
list_address_book
List saved addresses
list_connected_carriers
List connected carriers
list_contacts
List logistics contacts
list_freight_quotes
List recent quotes
list_item_catalog
List commonly shipped items
list_shipments
List freight shipments
list_webhooks
List active webhooks
request_rates
Request freight rates
Example Prompts for Freightview in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Freightview immediately.
"List my 5 most recent shipments and their current transit status."
"Request freight rates from 60601 to 90210 for a standard pallet."
"Show me all carriers currently connected to my account."
Troubleshooting Freightview MCP Server with Mastra AI
Common issues when connecting Freightview to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpFreightview + Mastra AI FAQ
Common questions about integrating Freightview MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
Connect Freightview with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Freightview to Mastra AI
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.