How to Use the Depreciation Calculator MCP in LlamaIndex

Q: What's required to connect the Depreciation Calculator to LlamaIndex?

You'll need the llama-index-tools-mcp package. You instantiate a BasicMCPClient with the server URL and wrap it in an McpToolSpec. Then you can convert it to a tool list for your agent.

Augment LlamaIndex queries with real-time depreciation calculations and build a knowledge base of financial data.

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Connect Depreciation Calculator MCP to LlamaIndex

Create your Vinkius account to connect Depreciation Calculator to LlamaIndex — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Depreciation Calculator with LlamaIndex

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Index Financial Calculations

This isn't just about running a one-off calculation. With LlamaIndex, you can automatically index the results of every depreciation calculation. Your RAG application now has a searchable history of financial modeling. For instance, query "what was the year 2 depreciation for the new server rack?" and LlamaIndex can find the answer from past `calculate_straight_line` tool calls. It grounds your financial queries in actual, calculated data.

Ground RAG in Financial Truth

Stop your financial Q&A bots from hallucinating numbers. By giving your LlamaIndex agent access to this MCP, it can answer questions by running live calculations. Ask it to compare two depreciation strategies, and it can invoke `calculate_sum_of_years_digits` and `calculate_declining_balance`, then use the real outputs to form its answer. It's a direct line to accurate financial math.

Combine Documents and Live MCP Server Data

The real power of LlamaIndex is combining data sources. Ingest your company's asset purchase orders as documents, then connect to this MCP Server. Now your agent can read the cost and purchase date from a PDF, then use this live tool to calculate its current depreciated value. Your queries can span both static documents and dynamic financial models.

Setup guide

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

You can build a RAG system that ingests asset lists and uses the Depreciation Calculator to provide real-time valuation. Ask your agent "show me all assets with less than $1000 book value" and it can calculate and filter on the fly.

Absolutely. The calculator can act as a tool in your pipeline. A query might first retrieve asset details from a vector store, then pass those details to the calculator tool to get a final value.

You'll need the `llama-index-tools-mcp` package. You instantiate a `BasicMCPClient` with the server URL and wrap it in an `McpToolSpec`. Then you can convert it to a tool list for your agent.

Yes, because this MCP separates the logic. If tax laws change or you need to add a new depreciation method, you only update the MCP. Your LlamaIndex application doesn't need to be changed or redeployed.

The MCP only sees the specific inputs for each calculation, like asset cost, salvage value, and asset life. It doesn't have access to your vector database or the content of your documents. Your data's privacy is maintained at the source.

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