Can my AI automatically find an available room for tomorrow and book it?

Yes. While your agent can list existing schedules across specific dates using ISO 8601 timeframes, it can dynamically cross-reference that with your list of available spaces. Once a gap is confirmed, the agent will prompt the booking creation tool linking your user ID to instantly reserve the room.

How will my AI know which space ID to book if I only know its name?

You can simply mention the plain name (e.g., 'Book the Innovation Boardroom'). The agent will intelligently call the 'list_spaces' tool in the background first, match your requested string to the correct internal resource ID, and generate the final reservation seamlessly.

Can I bulk cancel multiple reservations if an event reschedules?

Absolutely. You can request your AI to 'list all bookings for Monday', ask it to filter down to specific ones based on timeframe or assignee, and instruct it to execute a deletion for each matching reservation sequentially.

Skedda MCP Server for LlamaIndex 9 tools — connect in under 2 minutes

Name: Skedda
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 9 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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 Skedda. "
            "You have 9 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Skedda?"
    )
    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 Skedda MCP Server

Connect your Skedda workspace to any AI agent to completely fully automate facility management and space scheduling. Handle your entire booking lifecycle through natural language conversations.

LlamaIndex agents combine Skedda tool responses with indexed documents for comprehensive, grounded answers. Connect 9 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

Space & Venue Discovery — List all available physical spaces, venues, and their categorized groups (e.g., Office Hot Desks, Boardrooms)
Booking Operations — Retrieve your current schedule, or instantly create, update, and delete reservations natively
User Management — Look up fellow employees, customers, or members in the directory to assign them to bookings
Availability Tracking — Filter your list of reservations by specific timeframes (ISO 8601) to identify empty slots

The Skedda MCP Server exposes 9 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 Skedda to LlamaIndex via MCP

Follow these steps to integrate the Skedda 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 9 tools from Skedda

Why Use LlamaIndex with the Skedda MCP Server

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

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

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

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

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

Skedda + LlamaIndex Use Cases

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

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

Data enrichment: query Skedda 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 Skedda for fresh data

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

Skedda MCP Tools for LlamaIndex (9)

These 9 tools become available when you connect Skedda to LlamaIndex via MCP:

create_booking

Requires space ID, user ID, and start/end times. Creates a new booking

delete_booking

This action is irreversible. Permanently deletes a booking

get_booking_details

Retrieves details for a specific booking

list_bookings

You can filter by date range. Lists all bookings in Skedda

list_space_categories

g., "Meeting Rooms", "Desks"). Lists space categories

list_spaces

Lists all available spaces

list_users

Lists all users in the Skedda account

list_venues

Lists all venues

update_booking

Updates an existing booking

Example Prompts for Skedda in LlamaIndex

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

"List all meeting room zones and internal spaces we have available."

"Can you book 'Focus Pod 1' for tomorrow from 10:00 AM to 12:00 PM for user Marc Smith?"

"Cancel all bookings scheduled for the 'Training Center' on Friday."

Troubleshooting Skedda MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Skedda + LlamaIndex FAQ

Common questions about integrating Skedda 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 Skedda tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.