How to Use the NeetoCal MCP in LlamaIndex

Q: Can I filter NeetoCal tools for LlamaIndex?

You can. Use an allowedtools filter to restrict the agent to specific operations like getslots or listcalendars to keep your index clean and focused.

Ground your LlamaIndex knowledge base in real-time NeetoCal data for precise, hallucination-free scheduling.

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Connect NeetoCal MCP to LlamaIndex

Create your Vinkius account to connect NeetoCal to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup NeetoCal with LlamaIndex

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Index live NeetoCal data

Transform your booking history into a searchable knowledge base using LlamaIndex. Tool outputs from `list_bookings` become vectors for semantic retrieval. This means your agent answers questions about your calendar by querying your actual data. It stops relying on guesswork and starts relying on facts.

Ground agents in real-time availability

Use `get_availability` to feed current gaps into your RAG pipeline. The agent constructs answers based on what is actually open, not what it thinks is open. This creates a tighter loop between your documents and your calendar. Your users get accurate information every single time they ask for an appointment.

Unified tool and document access

Combine your internal documents with the NeetoCal toolset. Your agent searches your PDFs for policy info and then calls `create_booking` to finalize the meeting. This merges static knowledge with live API actions. You get a single interface that handles both information retrieval and calendar management.

Setup guide

Set up NeetoCal MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all NeetoCal MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to NeetoCal tools.",
)
response = await agent.run("List recent NeetoCal data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by NeetoCal. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about NeetoCal MCP in LlamaIndex

Absolutely. Once you run the tools, the results are indexed into your vector store. You can then perform semantic searches over your past booking history.

It uses the McpToolSpec to map tool outputs to your index. This allows the agent to ingest the response from `get_booking` and store it for future reference.

You can. Use an allowed_tools filter to restrict the agent to specific operations like `get_slots` or `list_calendars` to keep your index clean and focused.

It provides real-time access. Every time your agent queries the index, it pulls the most recent data directly from the NeetoCal API endpoints.

Yes. The Vinkius infrastructure ensures your data remains isolated. Your index only contains the information you explicitly pass into it via the tool responses.

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