How to Use the ISS Calculator MCP in LlamaIndex

Index Brazilian tax logic directly into your LlamaIndex MCP knowledge base.

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Connect ISS Calculator MCP to LlamaIndex

Create your Vinkius account to connect ISS 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 ISS Calculator with LlamaIndex

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Ground tax answers in real data

The `get_applicable_rate` tool pulls precise municipal percentages so your RAG application stops hallucinating tax brackets. Your query engine retrieves the exact local rule instead of guessing based on outdated training data. You index these API responses alongside your internal company policy documents. When a user asks about billing a client in São Paulo, the engine cross-references the live municipal rate with your corporate guidelines.

Index withholding mandates via MCP

Connecting `check_withholding_status` lets your system determine who actually pays the government. It checks the service category against federal and local withholding mandates. Developers build RAG pipelines that combine these withholding rules with vendor contracts. Your semantic search can now flag which subcontractors require tax retention before payment.

Store computed tax liabilities

Your application runs `calculate_tax_liability` to generate the final payable amount. The engine processes the base invoice value against the specific service rules. LlamaIndex stores this computed output in your vector store for future audits. Financial teams query past sessions to understand exactly how a specific tax burden was calculated three months ago.

Setup guide

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

Install llama-index-tools-mcp via pip. Pass the BasicMCPClient to your McpToolSpec to expose the functions to your query engine.

The framework indexes the API outputs into your vector store. You query the semantic index later to find historical tax decisions.

This MCP integrates municipal tax logic natively into your RAG pipeline. Your agents combine live tax math with unstructured contract data in one step.

The system handles any valid Brazilian city code. You pass the location parameter and the index retrieves the corresponding local tax law.

Your RAG pipeline only transmits the base calculation numbers and service codes to the MCP. We discard all mathematical inputs immediately after returning the liability result.

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