How to Use the Fuel Cost Calculator MCP in LlamaIndex

Index trip cost calculations and fuel efficiency data directly into your LlamaIndex knowledge base.

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Connect Fuel Cost Calculator MCP to LlamaIndex

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Setup Fuel Cost Calculator with LlamaIndex

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Index trip costs into your LlamaIndex RAG

Your LlamaIndex agent uses `calculate_trip_cost` to generate live pricing data for specific routes. LlamaIndex takes this fuel output and indexes it directly into your vector store. This turns transient fuel calculations into searchable LlamaIndex knowledge. Your LlamaIndex agent can query past trip expenses to answer future budget questions.

Query fuel efficiency recommendations via MCP Server

Call `compare_fuel_efficiency` to retrieve value comparisons between ethanol and gas within your LlamaIndex pipeline. The LlamaIndex agent stores the resulting fuel value metrics inside the document index. When LlamaIndex users ask about fuel economy trends, the system queries this indexed fuel data instead of making redundant API calls.

Build a knowledge base of trip summaries in LlamaIndex

Your LlamaIndex pipeline calls `get_trip_summary` to pull a complete overview of travel expenses and recommendations. The LlamaIndex tool output is structured for immediate indexing. This allows your LlamaIndex RAG application to ground its answers in verified route math, eliminating hallucinations about travel costs.

Setup guide

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

The LlamaIndex framework indexes the Fuel Cost Calculator outputs into a vector store. This allows your LlamaIndex agent to perform semantic searches over past route calculations.

Yes, you load the client, convert the Fuel Cost Calculator tools to tool specs, and pass them to the LlamaIndex FunctionAgent. The LlamaIndex agent will call the calculator whenever a user asks about trip budgets.

You can use the allowed tools filter during LlamaIndex initialization of the Fuel Cost Calculator. This restricts your LlamaIndex agent to only the specific calculation tools you want to expose.

Yes, by saving the Fuel Cost Calculator results to your LlamaIndex index, you can run vector queries. The LlamaIndex agent finds similar past trips to estimate costs so you don't run new calculations.

Absolutely. All route distances, fuel prices, and calculations are processed directly inside your local LlamaIndex pipeline. No data is sent to external servers for storage, keeping your LlamaIndex metrics secure.

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