How to Use the Arcadia Plug MCP in LlamaIndex

Q: Can I index data from this server into a LlamaIndex vector database?

Yes. You can run liststatements to fetch billing data, parse the text, and write it directly to any vector store supported by LlamaIndex.

Q: How does Arcadia Plug prevent hallucinations in LlamaIndex?

The getstatement tool provides exact, verifiable billing figures. Your agent bases its responses on this retrieved data rather than guessing historical energy costs.

Q: Can I filter which Arcadia Plug tools my LlamaIndex agent can access?

Yes. Use the allowedtools filter when configuring your McpToolSpec to restrict the agent to specific tools like listmeters while blocking credential access.

Q: How is my utility account security maintained when running Arcadia Plug?

Your account connections retrieved via listaccounts are secured using Vinkius's zero-trust MCP sandbox. The LlamaIndex runtime only receives structured JSON output, meaning your raw API keys and database credentials are never exposed directly to the LLM.

Index live utility bills and meter data from Arcadia Plug directly into your LlamaIndex vector store.

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Connect Arcadia Plug MCP to LlamaIndex

Create your Vinkius account to connect Arcadia Plug 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 Arcadia Plug with LlamaIndex

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Index Utility Statements for LlamaIndex RAG

The `list_statements` tool fetches your organization's historical energy bills so your agent can index them for semantic search. LlamaIndex ingestion pipelines convert these raw statements into searchable text nodes immediately. Users can then query their energy history using natural language. The agent retrieves the relevant chunked billing data, eliminating hallucinations by grounding answers in actual Arcadia records.

Ground Agent Decisions with Arcadia Plug MCP Server

Checking connection health with `get_account_check` prevents your LlamaIndex agent from querying stale or disconnected utility accounts. This check runs before any RAG retrieval step to ensure your data index remains accurate. Combine this check with `list_accounts` so your query engine knows exactly which utility providers are live. You don't waste LLM tokens indexing broken connections.

Query Meter Metadata Semantically

Feeding hardware details via `list_meters` inserts physical meter specifications into your LlamaIndex document store. Your agent uses this data to answer complex questions about hardware distribution across different facilities. This MCP approach bridges the gap between raw hardware listings and your conversational interface. It makes utility infrastructure searchable without manual database migrations.

Setup guide

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

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Common questions about Arcadia Plug MCP in LlamaIndex

Install llama-index-tools-mcp and initialize the BasicMCPClient. Wrap the client in McpToolSpec and call to_tool_list_async to pass the tools to your FunctionAgent.

Yes. You can run list_statements to fetch billing data, parse the text, and write it directly to any vector store supported by LlamaIndex.

The get_statement tool provides exact, verifiable billing figures. Your agent bases its responses on this retrieved data rather than guessing historical energy costs.

Yes. Use the allowed_tools filter when configuring your McpToolSpec to restrict the agent to specific tools like list_meters while blocking credential access.

Your account connections retrieved via list_accounts are secured using Vinkius's zero-trust MCP sandbox. The LlamaIndex runtime only receives structured JSON output, meaning your raw API keys and database credentials are never exposed directly to the LLM.

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