ANEEL Dados Abertos MCP for AI. Query Brazilian Electricity Market Records
Works with every AI agent you already use
…and any MCP-compatible client








Connect to your AI in seconds.
ANEEL Dados Abertos connects your agent directly to the Brazilian National Electric Energy Agency's public data portal. Use it to list available energy datasets, inspect metadata for specific packages, get details on downloadable resources like CSV or PDF files, and query records across integrated electricity market datastores.
What your AI can do
Get package
Fetches full metadata for a single, specified ANEEL dataset package.
Get resource
Gets file metadata (like format and download URL) for a specific resource within a dataset.
List packages
Retrieves the names of all datasets available across the entire ANEEL portal.
Lists every dataset available in the ANEEL portal so you know exactly what information is public.
Retrieves detailed structural and organizational tags for a specific data package.
Gets file-specific metadata, including the format (CSV, PDF, XLS) and download URL for any resource within a dataset.
Filters and searches record sets directly inside the integrated ANEEL data resources using natural language queries.
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ANEEL Dados Abertos: 4 Tools
Use these four tools to query datasets, retrieve file details, list packages, and search specific energy records within the public portal.
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Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using ANEEL Dados Abertos on VinkiusGet Package
Fetches full metadata for a single, specified ANEEL dataset package.
Get Resource
Gets file metadata (like format and download URL) for a specific resource within a...
List Packages
Retrieves the names of all datasets available across the entire ANEEL portal.
Search Datastore
Executes a targeted search for records within an integrated ANEEL data resource.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 4 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Sifting through Brazilian energy records used to mean days of clicking tabs and downloading files.
Before this MCP, if you needed tariff information, you'd visit the ANEEL portal. You’d click on a dataset package, then scroll through dozens of resources—some PDFs, some XLS, some CSVs. You'd have to manually download each one and copy-paste the specific metrics into an analysis sheet just to compare three different regions.
With this MCP, your agent handles that entire workflow in minutes. It first finds the right data package using `list_packages`. Then it verifies all available files using `get_resource` and executes a targeted query with `search_datastore`, spitting out only the structured records you need.
Structured Querying with search_datastore
The biggest time sink was always synthesizing data across different file types. You'd run a query on one CSV, download the results, then repeat the whole process for another resource type to get a complete picture of operational metrics.
Now you direct the agent to the specific resource ID and ask it to search the datastore. The result is immediate: a filtered list of records that synthesize multiple data points into one usable output.
What your AI can actually do with this
This MCP lets you programmatically interrogate the massive dataset of Brazil’s electricity sector. Instead of clicking through dozens of web forms and manual dashboards to find tariff schedules or generation metrics, your agent handles the navigation. You start by listing all available data packages in the ANEEL portal; once you pinpoint a dataset, you can fetch its full metadata to understand what's included.
The system then allows you to drill down further, getting specific details about resources like download URLs for CSV files or PDFs. If you know the target resource and need an answer—say, 'How did tariffs change in São Paulo last quarter?'—the agent runs a direct query against the data records.
You'll connect this whole workflow through Vinkius, routing complex queries to your preferred AI client.
019e3864-4dd4-73ec-9046-ad30e9f7a09e Here's how it actually works
The bottom line is that you bypass manual web navigation by issuing specific commands through your AI client.
First, subscribe to this MCP. If your access requires it, you'll enter your specific ANEEL API Key.
Next, tell your AI client what data you need—for instance, 'List all available datasets.'
The agent executes the necessary tools to retrieve structured metadata or perform a record search, giving you actionable results.
Who is this actually for?
Energy consultants and data analysts who spend too much time manually navigating public government portals to track tariffs or generation metrics. This MCP gives them programmatic access to complex, structured records.
Retrieves regulatory data and infrastructure details about the Brazilian power grid without having to manually click through multiple governmental websites.
Quickly lists, filters, and compares energy tariffs or generation metrics across different states by querying structured records.
Integrates public electricity data into internal applications using structured queries via the AI agent's output.
What Changes When You Connect
Instead of manually browsing for datasets, the list_packages tool gives you an immediate inventory of all available electricity data packages.
You don't need to guess where a specific file is. Use get_resource to pinpoint download URLs and verify if the resource is CSV, PDF, or XLS.
Forget clicking through filters for tariffs. You can use search_datastore to run complex queries against records directly in the data store.
The get_package tool lets you inspect a dataset's full metadata—tags and organizational details—before committing to a large query.
This MCP handles the tedious, multi-step process of finding, verifying, and querying structured energy records programmatically.
See it in action
Comparing Regional Tariffs
An analyst needs to compare generation data across three different states. They first use list_packages to find the correct dataset, then use get_package to confirm it contains tariff information, and finally run a targeted query with search_datastore to filter by state code.
Finding Source Documentation
A developer needs to know how the historical distribution metrics are formatted. They use list_packages to find the main dataset, then call get_resource on that package to identify both the primary CSV file and any associated PDF manuals.
Auditing Operational Metrics
An energy consultant needs to see all records mentioning a specific substation ID. They use search_datastore, passing the resource ID and the target substation, getting an immediate list of relevant operational metrics.
The honest tradeoffs
Assume everything is in one place
Trying to guess if tariff data is in a CSV or a PDF without knowing which resource ID to check.
Always start by calling list_packages for the general inventory. Then, use get_resource on that package's metadata to see all available formats and URLs.
Over-relying on manual search
Manually downloading 10 different CSV files from various tabs just to find the single metric you need.
Use search_datastore. Pass the resource ID and your specific filter criteria (e.g., 'São Paulo' AND 'Q3') to get a filtered, targeted record set immediately.
Ignoring dataset structure
Running a search query without first verifying if the package is correct or if the data store is live.
Always run get_package after finding a promising name via list_packages. This confirms the metadata and ensures the tool can access the intended scope.
When It Fits, When It Doesn't
Use this MCP if your goal is to programmatically interrogate structured, public energy data from ANEEL. You need to know what datasets exist (list_packages), where the files are (get_resource), or you need to run a specific query on existing records (search_datastore). Don't use this if your goal is simply to browse the portal visually or if you only need a single, static document download; then, manual browsing might be faster. This MCP is for agents that execute multi-step data pipelines.
Questions you might have
How do I find out what datasets are available using get_package? +
get_package doesn't list all packages. To start, you must first use list_packages to get the full inventory of dataset names.
What is the difference between get_resource and search_datastore? +
get_resource tells you about a file (its format and URL). search_datastore actually runs a query against the data inside that resource.
Can I use list_packages to find specific tariff data? +
No. You must run list_packages first, then select a promising package name, and finally use get_package or search_datastore to actually extract the data.
Do I need an API key for search_datastore? +
Yes. If specific access is required by ANEEL, you must provide your API Key before attempting any resource query with search_datastore.
If I use `get_package` with a package ID that doesn't exist, what kind of error should I expect? +
The tool returns a structured API error message. This message details the failure reason, confirming whether the issue is an invalid identifier or if specific access permissions are missing for the dataset.
When running complex queries with `search_datastore`, how does it handle pagination to prevent massive data dumps? +
The search tool supports pagination using offset parameters. To pull all records, you must pass the next page token along with subsequent requests, ensuring you retrieve complete data sets without hitting size limits.
To successfully use `get_resource`, what two identifiers are required to pinpoint a specific file's metadata? +
You must supply both the dataset package ID and the unique resource ID. The tool combines these inputs to locate the exact data asset, confirming its format (CSV, PDF, or XLS) and providing its download URL.
What high-level context does `list_packages` provide beyond just listing dataset names? +
It returns key metadata for each listed package. You get the official description and the originating organization within ANEEL, helping you quickly assess relevance before running a deep query.
How can I find the specific ID for a dataset like 'Tarifas das Distribuidoras'? +
You can use the list_packages tool to see all available names. Once you identify the name, use get_package with that ID to see all its internal resources and metadata.
Can I search for a specific company name inside a CSV resource? +
Yes! If the resource is part of the DataStore, use the search_datastore tool. You can provide the resource_id and use the q parameter for a full-text search or filters for specific field matching.
What information is included in the resource metadata? +
The get_resource tool returns the file format (CSV, PDF, etc.), the creation date, the last modification date, and the direct download URL for the data file.
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