Siteminder MCP Server for LlamaIndexGive LlamaIndex instant access to 18 tools to Cp Cancel Reservation, Cp Confirm Reservation, Cp Get Property, and more

Name: Siteminder
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

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LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Siteminder as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The Siteminder MCP Server for LlamaIndex is a standout in the Ecommerce category — giving your AI agent 18 tools to work with, ready to go from day one.

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python

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 Siteminder. "
            "You have 18 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Siteminder?"
    )
    print(response)

asyncio.run(main())

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* 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 Siteminder MCP Server

Connect your Siteminder account to any AI agent to streamline hotel distribution and reservation management through natural conversation.

LlamaIndex agents combine Siteminder tool responses with indexed documents for comprehensive, grounded answers. Connect 18 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

Property Search — Find properties by location, radius, and dates using Channels Plus (cp_search_properties)
Inventory & Rates — Access room types, rates, and quotes for specific properties (db_get_room_types, db_get_room_rates)
Reservation Lifecycle — Lock, confirm, modify, and cancel bookings directly through the agent (cp_lock_reservation, cp_confirm_reservation)
Booking History — Retrieve and list historical reservations associated with your account (cp_list_reservations)
Direct Booking — List and inspect properties within your group using the Direct Booking API (db_list_properties)

The Siteminder MCP Server exposes 18 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 18 Siteminder tools available for LlamaIndex

When LlamaIndex connects to Siteminder through Vinkius, your AI agent gets direct access to every tool listed below — spanning hotel-management, booking-engine, inventory-sync, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

Cp cancel reservation on Siteminder

Cancel an existing reservation

Cp confirm reservation on Siteminder

Finalize booking with guest and payment details

Cp get property on Siteminder

Get property details via Channels Plus API

Cp list reservations on Siteminder

Retrieve historical bookings via Channels Plus API

Cp lock reservation on Siteminder

Create a 10-minute hold on inventory

Cp modify reservation on Siteminder

Modify an existing reservation

Cp search properties on Siteminder

Search properties via Channels Plus API

Db get property on Siteminder

Get property details via Direct Booking API

Db get quotes on Siteminder

Get pricing and availability for a specific stay

Db get room rates on Siteminder

Get room rates for a property via Direct Booking API

Db get room types on Siteminder

Get room types for a property via Direct Booking API

Db list properties on Siteminder

List all properties in the group via Direct Booking API

smx

Smx get availability on Siteminder

Query inventory for a date range via SMX API

smx

Smx get rates on Siteminder

Query pricing for a date range via SMX API

smx

Smx list hotels on Siteminder

List connected properties for a publisher via SMX API

smx

Smx list publishers on Siteminder

List connected PMS providers via SMX API

smx

Smx list rate plans on Siteminder

List rate plans for a hotel via SMX API

smx

Smx list room types on Siteminder

List room types for a hotel via SMX API

Connect Siteminder to LlamaIndex via MCP

Follow these steps to wire Siteminder into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 18 tools from Siteminder

Why Use LlamaIndex with the Siteminder MCP Server

LlamaIndex provides unique advantages when paired with Siteminder through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Siteminder tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Siteminder tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Siteminder, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Siteminder tools were called, what data was returned, and how it influenced the final answer

Siteminder + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Siteminder MCP Server delivers measurable value.

Hybrid search: combine Siteminder real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Siteminder 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 Siteminder for fresh data

Analytical workflows: chain Siteminder queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Siteminder in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Siteminder immediately.

"Find hotels near lat 40.7128, long -74.0060 within a 5km radius for next weekend."

"Get the room types and rates for property UUID '123-abc-456'."

"Show me the history of bookings for my account."

Troubleshooting Siteminder MCP Server with LlamaIndex

Common issues when connecting Siteminder to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Siteminder + LlamaIndex FAQ

Common questions about integrating Siteminder MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Siteminder tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.