How to Use the Days Between Dates Calculator MCP in LlamaIndex

Index your project timelines in LlamaIndex by querying precise date intervals and holiday status via this MCP.

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Connect Days Between Dates Calculator MCP to LlamaIndex

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Setup Days Between Dates Calculator with LlamaIndex

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Index business day calculations

Turn the result of `count_business_days` into a searchable vector entry. Your LlamaIndex application remembers these intervals for future queries about project velocity. This creates a knowledge base where your agent retrieves past calculations instead of recalculating them. You get faster answers grounded in your specific historical data.

Store detailed temporal breakdowns

Map the output of `get_date_breakdown` to your documents for better semantic search. Your agent can then answer questions about the specific structure of a project timeline. This makes your RAG pipeline smarter by including calculated time gaps in the indexed context. The agent connects these findings to your existing documents.

Ground holiday logic in your index

Check if a date is a holiday with `verify_holiday_status` and add the result to your searchable records. Your LlamaIndex agent uses this to filter out invalid dates from its knowledge base. It ensures your agent understands regional constraints when building schedules. You gain a reliable way to query whether specific days are suitable for work.

Setup guide

Set up Days Between Dates Calculator 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 Days Between Dates Calculator 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 Days Between Dates Calculator tools.",
)
response = await agent.run("List recent Days Between Dates Calculator 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 Days Between Dates. 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 Days Between Dates Calculator MCP in LlamaIndex

You wrap the tools in a specification object and pass them to your agent. This allows the framework to index the tool outputs as part of your knowledge base.

Yes, by indexing the tool outputs, your agent creates a searchable history of past date calculations. This helps in retrieving specific timeline data later.

You can use the tool to generate constraints that your agent applies to search queries. This narrows down results to specific working windows.

The client handles async execution, allowing your agents to query date data without blocking the index build process.

Your information is processed in memory and is never shared with third parties. This MCP treats your calendar inputs as private ephemeral data.

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