How to Use the Corrently Regional Green Index MCP in LlamaIndex

Index grid forecasts into LlamaIndex to build RAG apps that ground your agent's decisions in live energy market data.

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Connect Corrently Regional Green Index MCP to LlamaIndex

Create your Vinkius account to connect Corrently Regional Green Index 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 Corrently Regional Green Index with LlamaIndex

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Index grid data in LlamaIndex

Pipe the results of `get_regional_green_index` into your LlamaIndex vector store for semantic search. Your agent retrieves past grid forecasts alongside your documents to ground its output in historical context. This turns transient API responses into a searchable knowledge base. Your agent finds patterns in energy availability by querying the indexed tool data during its reasoning process.

Ground decisions with market data

Use `get_energy_market_data` to feed live price points into your RAG pipeline. Your application compares current market rates against your document store to provide grounded, data-backed answers. Your agent doesn't hallucinate about grid status because it references the indexed tool outputs. This creates a reliable feedback loop where API data directly informs the responses generated.

Filter tool access in LlamaIndex

Restrict which MCP tools your agent can call to maintain strict control over your data retrieval. You set the `allowed_tools` parameter to ensure only the green index or market data tools are accessed. This prevents your agent from over-reaching during the RAG process. You keep your system focused by limiting the scope of available tools to only what is necessary for your energy analytics.

Setup guide

Set up Corrently Regional Green Index 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 Corrently Regional Green Index 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 Corrently Regional Green Index tools.",
)
response = await agent.run("List recent Corrently Regional Green Index data")

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Common questions about Corrently Regional Green Index MCP in LlamaIndex

Use the MCP tool spec to wrap the client and convert the tools into a list compatible with the FunctionAgent. This allows your agent to query the grid data as if it were a document.

LlamaIndex indexes the tool output into your vector store, allowing for persistent retrieval. You control how long that data remains relevant within your index.

The server only touches public grid forecast figures and regional pricing. Your vector store keeps this data isolated within your local or cloud-hosted environment.

The agent decides when to trigger the tools based on the user prompt. It then indexes the results to answer your specific energy-related questions.

The server provides ZIP-code-based electricity index values and energy market pricing. This information is treated as read-only input for your knowledge base.

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