Easyship MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Easyship as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Easyship. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Easyship?"
)
print(response)
asyncio.run(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 Easyship MCP Server
Integrate Easyship, the leading global shipping platform for e-commerce, directly into your AI workflow. Manage your cross-border shipments and carrier rates, track packages in real-time with detailed checkpoint logs, monitor available couriers and their service levels, and oversee your logistics operations using natural language.
LlamaIndex agents combine Easyship tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Shipment Oversight — List and retrieve detailed information and real-time status for all your global logistics shipments.
- Rate Intelligence — Request instant shipping quotes and estimated delivery times for various couriers based on parcel details.
- Tracking Monitoring — Monitor active shipments, resolving real-time transit statuses, courier events, and delivery receipts.
- Carrier Management — Access and monitor all available couriers and their specific service capability boundaries.
The Easyship MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex 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 Easyship to LlamaIndex via MCP
Follow these steps to integrate the Easyship MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Easyship
Why Use LlamaIndex with the Easyship MCP Server
LlamaIndex provides unique advantages when paired with Easyship through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Easyship tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Easyship tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Easyship, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Easyship tools were called, what data was returned, and how it influenced the final answer
Easyship + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Easyship MCP Server delivers measurable value.
Hybrid search: combine Easyship real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Easyship to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Easyship for fresh data
Analytical workflows: chain Easyship queries with LlamaIndex's data connectors to build multi-source analytical reports
Easyship MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Easyship to LlamaIndex via MCP:
get_easyship_account_metadata
Retrieve metadata and limits for your Easyship account
get_shipment_details
Get detailed information and tracking for a specific shipment
get_shipping_rates
Request shipping rates for a potential shipment
list_available_couriers
List all available couriers and their service capability boundaries
list_failed_deliveries
Identify shipments that have failed delivery or encountered issues (mock logic)
list_in_transit_shipments
Identify shipments that are currently in transit with a courier
list_latest_shipments
Identify the most recently created or updated shipments
list_logistics_shipments
List all shipments in your Easyship account
quick_shipping_volume_audit
Retrieve a high-level summary of shipment activity and success rates
search_shipments_by_reference
Search for shipments using a reference ID or keyword
Example Prompts for Easyship in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Easyship immediately.
"List the most recent global shipments."
"Get shipping rates from USA to France for a 1kg parcel."
"Check the status of shipment 'ES-12345678'."
Troubleshooting Easyship MCP Server with LlamaIndex
Common issues when connecting Easyship to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpEasyship + LlamaIndex FAQ
Common questions about integrating Easyship MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Easyship 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 Easyship to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.