How to Use the ANEEL Dados Abertos MCP in LangChain

Q: How do I search for energy records using ANEEL Dados Abertos with LangChain?

Use the searchdatastore tool within your agent definition. Pass your query string as the input parameter to pull relevant records directly into your chain.

Chain ANEEL Dados Abertos calls directly into your LangChain agents to process Brazilian power sector data automatically.

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Connect ANEEL Dados Abertos MCP to LangChain

Create your Vinkius account to connect ANEEL Dados Abertos to LangChain 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 ANEEL Dados Abertos with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Build multi-step reasoning with LangChain

Feed the output of `list_packages` directly into subsequent chain components to filter through electricity datasets. Your agent handles the logic flow without manual intervention. LangChain tracks every step of the request. You see exactly how the agent decides to use `get_package` based on the initial search results.

Automate data retrieval for your pipelines

Connect this MCP Server to your LangGraph workflows to pull raw records from the ANEEL portal. The tools act as native nodes in your execution graph. Use `search_datastore` to grab specific records for your RAG pipeline. It keeps your data fresh by pulling directly from the source during runtime.

Observe your ANEEL tool usage

Monitor every call to `get_resource` through your existing tracing setup. You get full visibility into latency and token usage for every query. Debug how your agent interacts with the portal by inspecting the input and output schemas. It makes building complex energy data agents much faster.

Setup guide

Set up ANEEL Dados Abertos MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes ANEEL Dados Abertos tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "aneel-dados-abertos-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent ANEEL Dados Abertos transactions"
    })
    print(result["messages"][-1].content)

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Common questions about ANEEL Dados Abertos MCP in LangChain

Use the `search_datastore` tool within your agent definition. Pass your query string as the input parameter to pull relevant records directly into your chain.

Yes, but you should chain it with processing tools to manage memory. Use `get_resource` to isolate specific file downloads before your agent attempts to parse the content.

Absolutely. You can maintain conversation context by using a persistent session with the client. This allows the agent to recall previous dataset metadata requests.

It is. You can pass these tools to any agent in your ensemble, allowing specific agents to specialize in querying the Brazilian electricity portal.

This server only performs read operations on public Brazilian power sector metadata. Your data remains local to your client environment and is never logged by Vinkius.

Use it with your favorite AI tools

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