How to Use the MakePlans MCP in LlamaIndex

Q: Is it possible to filter tools in LlamaIndex when using MakePlans?

You can use the allowedtools filter to restrict which operations the agent performs. This prevents the agent from accessing sensitive admin tools while allowing it to read appointment data.

Index your live MakePlans appointment data directly into LlamaIndex for semantic search and retrieval.

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Connect MakePlans MCP to LlamaIndex

Create your Vinkius account to connect MakePlans 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 MakePlans with LlamaIndex

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Ground your LlamaIndex RAG in live booking data

Convert the output of `list_appointments` into indexed knowledge. LlamaIndex ingests these records so your RAG application can answer questions about past or future bookings without hallucinating details. Perform semantic searches across your entire booking history. By turning API responses into searchable vectors, your system provides accurate summaries of customer interactions.

Query available slots with semantic precision

Use `find_available_slots` as part of a tool spec that LlamaIndex can query dynamically. The agent identifies the user's intent and fetches the right slots based on your service requirements. Ground your booking suggestions in live data from `list_available_services`. This keeps your knowledge base updated with the current state of your resources.

Access booking resources as knowledge nodes

Incorporate `list_booking_resources` into your data index to help the agent understand staff availability or room capacity. This metadata acts as context for every query your agent processes. Keep your documentation and operational data in one searchable index. The MCP integration ensures that live API data is never out of sync with your indexed knowledge.

Setup guide

Set up MakePlans 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 MakePlans 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 MakePlans tools.",
)
response = await agent.run("List recent MakePlans 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 MakePlans. 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 MakePlans MCP in LlamaIndex

Use the BasicMCPClient to connect and convert the tools into a spec. Once indexed, your RAG agents can query the API results just like any other document.

Yes. By indexing the tool output, your agent retrieves grounded information about specific appointments instead of guessing based on static training data.

You can use the allowed_tools filter to restrict which operations the agent performs. This prevents the agent from accessing sensitive admin tools while allowing it to read appointment data.

Data is encrypted during transit and access is restricted to the specific tools you authorize. Your appointment records are processed within the secure Vinkius sandbox.

You can refresh your index periodically to pull the latest data from the API. This ensures your agent always works with current appointment and customer information.

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