Presenton MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Check Presenton Status, Delete Presentation, Duplicate Presentation, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Presenton 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 App Connector for LlamaIndex
The Presenton app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Presenton. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Presenton?"
)
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 Presenton MCP Server
Connect your Presenton account to any AI agent and simplify your presentation workflows through natural conversation.
LlamaIndex agents combine Presenton 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
- AI Deck Generation — Create complete presentation decks from text prompts, adjusting tone and slide count
- Export Management — Retrieve download links for your presentations in PPTX or PDF formats
- Template Catalog — List available AI-optimized templates to find the best look for your slides
- History Tracking — Monitor and manage your past presentations directly from your agent
The Presenton 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.
All 12 Presenton tools available for LlamaIndex
When LlamaIndex connects to Presenton through Vinkius, your AI agent gets direct access to every tool listed below — spanning presentation-software, ai-generation, slide-decks, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Verify connectivity
Delete a presentation
Duplicate a presentation
Export a presentation
Generate a presentation
Get account
Get presentation
Get template
List presentations
List templates
List themes
Update a presentation
Connect Presenton to LlamaIndex via MCP
Follow these steps to wire Presenton into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Presenton MCP Server
LlamaIndex provides unique advantages when paired with Presenton through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Presenton tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Presenton tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Presenton, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Presenton tools were called, what data was returned, and how it influenced the final answer
Presenton + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Presenton MCP Server delivers measurable value.
Hybrid search: combine Presenton real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Presenton 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 Presenton for fresh data
Analytical workflows: chain Presenton queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Presenton in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Presenton immediately.
"Create a 5-slide presentation about 'Sustainable Farming'."
"Generate a professional sales pitch presentation for the Q3 enterprise product launch."
"List all presentation templates available in my account and their usage statistics."
Troubleshooting Presenton MCP Server with LlamaIndex
Common issues when connecting Presenton to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPresenton + LlamaIndex FAQ
Common questions about integrating Presenton MCP Server with LlamaIndex.