How to Use the FedEx MCP in Mastra AI
Build resilient logistics workflows in Mastra AI with automatic retries and conditional branching for FedEx shipments.
Works with every AI agent you already use
…and any MCP-compatible client
Connect FedEx MCP to Mastra AI
Create your Vinkius account to connect FedEx to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Resilient FedEx Label Creation Workflows in Mastra AI
Shipping labels cannot fail silently in automated workflows. With this MCP Server, your Mastra AI agents can execute `create_shipment` inside structured workflows that automatically retry if the FedEx API drops. If the initial FedEx API call fails, the Mastra AI framework applies exponential backoff to ensure your shipping labels get generated without manual intervention. Your automated warehouse operations keep running smoothly.
Conditional Routing Based on Service Availability
Let your Mastra AI agents make smart logistics decisions on the fly. Mastra AI can use `check_service_availability` to see if overnight FedEx shipping is active for a destination zip code before booking. If Express isn't available, the Mastra AI workflow branches to check Ground rates via `get_rates` and updates your database automatically. You never promise FedEx shipping speeds you can't deliver.
Human-in-the-Loop Verification for Address Failures
When a FedEx address looks suspicious, don't just guess. Mastra AI lets you pause execution when `validate_address` returns an unresolved status, prompting a human operator to confirm. Once the operator corrects the street details, the Mastra AI workflow resumes to trigger `create_shipment` and find a nearby drop-off via `find_locations`.
Set up FedEx MCP in Mastra AI
Prerequisites
- Node.js 18+ and a TypeScript project
-
@mastra/mcp+@mastra/corepackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
npm install @mastra/mcp @mastra/coreplus your preferred model provider (e.g.@ai-sdk/openai). - 2
Configure the MCPClient
Create an
MCPClientwith your Vinkius endpoint as aURLobject. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Discover and inject tools
Call
mcpClient.listTools()and spread the result into your agent'stoolsobject. All FedEx tools become native Mastra tools. - 4
Run with any model
Swap
openai("gpt-4o")for any AI SDK-compatible provider. Callagent.generate()and the agent routes tool calls through MCP automatically.
import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";
const mcpClient = new MCPClient({
id: "fedex-mcp-client",
servers: {
"fedex-mcp": {
url: new URL(
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
),
},
},
});
const agent = new Agent({
name: "FedEx Agent",
model: openai("gpt-4o"),
instructions: "You have access to FedEx tools.",
tools: {
...(await mcpClient.listTools()),
},
});
const result = await agent.generate(
"List recent FedEx transactions"
);
console.log(result.text); Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by FedEx. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about FedEx MCP in Mastra AI
Use it with your favorite AI tools
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