Ezus MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Ezus 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 Ezus. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Ezus?"
)
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 Ezus MCP Server
Connect your Ezus travel management account to any AI agent and take full control of your agency's workflows through natural conversation.
LlamaIndex agents combine Ezus tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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
- Project Management — List, fetch, and upsert travel projects directly from the Ezus cloud
- Client & Supplier CRM — Query client details and manage your network of suppliers with ease
- Product Catalog — Access and inspect your travel products and packages stored in the Ezus catalog
- Financial Overview — List and inspect invoices to keep track of your agency's billing and financial status
- User Profiling — Retrieve the underlying credentials and profile information of your agent's API user
The Ezus MCP Server exposes 12 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 Ezus to LlamaIndex via MCP
Follow these steps to integrate the Ezus 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 12 tools from Ezus
Why Use LlamaIndex with the Ezus MCP Server
LlamaIndex provides unique advantages when paired with Ezus through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Ezus tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Ezus tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Ezus, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Ezus tools were called, what data was returned, and how it influenced the final answer
Ezus + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Ezus MCP Server delivers measurable value.
Hybrid search: combine Ezus real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Ezus 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 Ezus for fresh data
Analytical workflows: chain Ezus queries with LlamaIndex's data connectors to build multi-source analytical reports
Ezus MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Ezus to LlamaIndex via MCP:
get_client
Get a specific Ezus client by ID
get_invoice
Get a specific Ezus invoice by ID
get_me
Get current Ezus user profile
get_product
Get a specific Ezus product by ID
get_project
Get a specific Ezus project by ID
get_supplier
Get a specific Ezus supplier by ID
list_clients
List all Ezus clients
list_invoices
List all Ezus invoices
list_products
List all Ezus products
list_projects
List all Ezus projects
list_suppliers
List all Ezus suppliers
upsert_project
Create or update an Ezus project
Example Prompts for Ezus in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Ezus immediately.
"List my recent travel projects on Ezus."
"Show me the details for client ID 12345."
"Get all products available in the catalog."
Troubleshooting Ezus MCP Server with LlamaIndex
Common issues when connecting Ezus to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpEzus + LlamaIndex FAQ
Common questions about integrating Ezus 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 Ezus 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 Ezus to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.