How to Use the Fundamental Math MCP in LlamaIndex

Q: How do I register Fundamental Math in LlamaIndex?

Install llama-index-tools-mcp and initialize the BasicMCPClient. Convert the server tools to a list with totoollistasync() and pass them to your LlamaIndex FunctionAgent.

Q: Can LlamaIndex index outputs from Fundamental Math?

Yes. You can capture the output of tools like calculateruleofthree or calculatepercentage and write them directly to your vector index for semantic retrieval.

Index exact local math results directly into your LlamaIndex vector stores to ground your RAG pipelines in real numbers.

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Connect Fundamental Math MCP to LlamaIndex

Create your Vinkius account to connect Fundamental Math 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 Fundamental Math with LlamaIndex

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Ground LlamaIndex RAG with exact math

Integrating `calculate_percentage` and `calculate_rule_of_three` into your LlamaIndex pipeline prevents hallucinated statistics in your search results. When indexing documents, use these tools to check raw metrics before they enter your vector store. This MCP Server executes locally to calculate values on the fly. Your query engine can get these exact calculations instead of relying on an LLM to guess percentages.

Index math outputs for semantic search

The `calculate_power` and `calculate_square_root` tools turn mathematical operations into searchable knowledge for LlamaIndex. Pass outputs straight into your document store to build a history of exact computations. Your agents can look up past calculations semantically. This avoids recalculating complex values and provides a clear audit trail of all mathematical steps.

Local math tools for LlamaIndex agents

Running `calculate_factorial` locally speeds up your LlamaIndex data agents by bypassing remote math APIs. This local engine handles calculations instantly, returning precise integers directly to your pipeline. You load the tools using the LlamaIndex MCP tool spec. The agent selects the correct tool based on the user's query, ensuring fast, offline arithmetic execution.

Setup guide

Set up Fundamental Math 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 Fundamental Math 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 Fundamental Math tools.",
)
response = await agent.run("List recent Fundamental Math data")

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Common questions about Fundamental Math MCP in LlamaIndex

Install `llama-index-tools-mcp` and initialize the `BasicMCPClient`. Convert the server tools to a list with `to_tool_list_async()` and pass them to your LlamaIndex `FunctionAgent`.

Yes. You can capture the output of tools like `calculate_rule_of_three` or `calculate_percentage` and write them directly to your vector index for semantic retrieval.

Instead of letting the LLM guess math during synthesis, LlamaIndex routes calculations to `calculate_power` or `calculate_square_root`. This forces the agent to use deterministic local math.

No, all calculations run locally inside the Vinkius sandbox. Your agent can compute factorials and percentages completely offline without relying on cloud endpoints.

The MCP Server processes your raw numbers locally in an isolated memory space. No external telemetry or calculation logs are sent over the network, protecting your proprietary metrics.

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