Datos Abiertos MCP for AI. Query regional public data via natural language.
Works with every AI agent you already use
…and any MCP-compatible client








Connect to your AI in seconds.
Datos Abiertos Castilla-La Mancha lets your AI agent access public data from the Spanish region. It helps you list all available datasets, find specific resources like CSVs or JSON files, and search records directly within a table without downloading massive files.
What your AI can do
Get dataset
Retrieves detailed information about a single, named dataset from the portal.
Get resource
Gets metadata for a specific file or resource linked to a dataset.
List datasets
Lists all available datasets currently published on the portal in bulk.
See a full list of every dataset published on the portal using simple identifiers or topic tags.
Fetch detailed information about any dataset, including when it was last updated and who maintains it.
Locate the direct links or metadata for physical resources within a dataset (like CSVs or PDFs).
Filter and search through structured rows of data inside a resource without downloading the entire file.
Explore all available categories or tags (e.g., 'environment' or 'education') to narrow down your search results.
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Datos Abiertos Castilla-La Mancha: 5 Tools
Use these five tools to manage data discovery tasks, from listing all available topics to running deep searches within structured records.
Make your AI actually useful.
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 Datos Abiertos Castilla-La Mancha on VinkiusGet Dataset
Retrieves detailed information about a single, named dataset from the portal.
Get Resource
Gets metadata for a specific file or resource linked to a dataset.
List Datasets
Lists all available datasets currently published on the portal in bulk.
List Tags
Retrieves a list of organizational tags and categories used across the entire data...
Search Datastore
Searches and filters records directly inside a structured database resource without...
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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 5 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Sifting through regional government websites is slow work.
Today, finding data requires a lot of manual labor. You have to navigate the portal structure: click on 'Health,' then select 'Dataset X,' then find the specific report you need. This process often forces you to download massive CSV files and spend hours just figuring out which tab contains the right column headers.
With this MCP, you simply talk to your agent. You tell it what data you want—like records about air quality in a specific town. Your agent handles all the portal navigation using tools like `list_tags` or `get_dataset`. You get an immediate answer, not a folder of files.
Getting structured answers with Datos Abiertos Castilla-La Mancha.
The manual steps that disappear are the initial browsing and the need for bulk downloads. You skip clicking through dozens of pages and you don't have to guess if a resource is JSON or CSV; the agent tells you upfront using `get_resource` details.
Now, your focus stays on analysis. Your agent provides precise records right in the chat window. It’s immediate, verifiable data ready for your next step.
What your AI can actually do with this
Need to research regional trends in health, environment, or economy? Instead of navigating complex government portals with dozens of clicks, you talk to your AI agent. This MCP connects straight to the official Castilla-La Mancha Open Data repository. Your agent handles all the discovery work: listing every available dataset, checking details on specific reports, and finding exactly which file format (CSV, JSON) you need.
It’s better than manually browsing a portal. If you're working with Vinkius, your agent can query records directly inside a data table using natural language—you don't have to download the whole thing just to find five rows of information. This means you spend time analyzing data, not figuring out how the government website is organized.
019e3886-fb1c-739d-a91d-b87acd91006d Here's how it actually works
The bottom line is you ask a question, and the MCP gets the specific public record answer for you.
Subscribe to this MCP and enter the necessary API Key into your agent client.
Tell your AI agent what you need, for example: 'List all datasets related to water quality.'
The agent executes the query against the portal's data structure and returns actionable results directly in the chat interface.
Who is this actually for?
Researchers who need to analyze large volumes of governmental statistics. Data developers integrating open data into apps. Anyone tired of wasting time clicking through complicated government websites just to find a single table.
Uses the MCP to quickly sample regional statistics for reports, using tools like list_datasets and search_datastore to pinpoint necessary fields.
Relies on natural language queries to explore public records across topics like health or economy without needing to know the underlying portal structure.
Tests and integrates public data sources into applications by using the AI agent to execute specific metadata checks (get_dataset) before writing code.
What Changes When You Connect
Stop downloading massive files. You can use search_datastore to filter records inside a table, giving you only the specific rows you need.
Instantly check dataset details using get_dataset. Know when a report was last updated and who maintains it before you start your analysis.
You don't have to browse by category manually. Use list_tags to see every available topic tag, which helps narrow down complex research areas quickly.
Get an overview of all data sources right away with the list_datasets tool. This tells you exactly what type of regional statistics are available.
Find the exact file format you need (CSV, JSON) using get_resource. The agent gives you metadata for that specific resource link.
See it in action
Comparing health center data across regions
A researcher needs to compare public records from different years. They ask the agent to list_datasets first, find all 'health' datasets, and then use get_dataset on each one to check for consistent fields before starting their analysis.
Finding specific budget figures
A developer needs a figure from the 2024 budget report. They tell their agent to search the relevant datastore using search_datastore, filtering by 'Municipio' and 'Año', getting the exact number without needing to open an Excel file.
Mapping out available research topics
A new team member wants to know what kind of public data exists. They ask the agent to use list_tags immediately, which provides a comprehensive list of all available organizational categories (e.g., 'environment', 'economy').
Verifying resource accessibility
A user knows they need data on air quality but isn't sure if the file is JSON or CSV. They ask the agent to get_resource for the dataset, and it provides metadata confirming all available formats.
The honest tradeoffs
Manual web portal browsing
The user spends 30 minutes clicking through menus, downloading a large ZIP file containing multiple sheets, and then manually figuring out which spreadsheet has the data they need.
Instead of downloading everything, ask your agent to search_datastore directly. The tool filters the records inside the resource based on criteria you provide in natural language.
Assuming a dataset contains all info
The user assumes that because they found a dataset via list_datasets, it has everything. They download and find only incomplete data.
Always run get_dataset first. This checks the metadata to confirm what fields are included, making sure you know exactly what you're getting.
Ignoring topics
The user starts their search without knowing if 'environment' or 'economy' data is available.
Start by running list_tags. This gives a quick map of the entire portal, letting you focus your query on proven topic areas.
When It Fits, When It Doesn't
Use this MCP when your goal is deep, structured research into established public records. You need to list datasets, check metadata, or filter tables based on tags or identifiers. Don't use it if you need real-time operational data (like current stock prices or live transaction logs). For those cases, look for specialized APIs that connect directly to transactional databases, not just open data portals. If your data source is a proprietary system with unique login requirements, this MCP won't help; you'll need an integration built specifically for that service.
Questions you might have
How do I find out what kind of data is available? (list_tags) +
You use list_tags. This tool pulls every active category and tag from the portal, giving you a quick map of all topics—from 'economy' to 'environment'—so you know where to focus your research.
If I want to search for specific records, should I use `search_datastore`? (search_datastore) +
Yes. Using search_datastore is the most efficient way. It lets you filter and query rows directly inside a resource file without forcing you to download gigabytes of data.
How do I check if a dataset is still current? (get_dataset) +
You use get_dataset. This tool retrieves the metadata, which includes details on the update frequency and who maintains it. It tells you if the data is trustworthy enough for your report.
I need to find a specific file format like GeoJSON. What do I use? (get_resource) +
Use get_resource. This tool finds details about physical files within a dataset, confirming the exact resource ID and available formats you're looking for.
What is the best way to start my research on regional data? (list_datasets) +
Start with list_datasets. This provides an immediate, comprehensive list of every dataset published. It gives you a high-level overview of all available topics and resources.
What should I do if I hit rate limits when using list_datasets? +
The system will provide a clear error message indicating the limit has been reached. To continue querying, you must either wait for the allotted time or configure your API key with higher usage quotas through the official data portal.
If I use get_dataset with an invalid ID, how does the agent handle it? +
The MCP will immediately return a specific error code and message instead of failing silently. Your AI client will receive this structured failure notification, letting you know exactly which dataset ID needs correction.
Can I filter results using search_datastore beyond simple field names? +
Yes, the agent allows complex filtering logic. You can specify filters based on multiple fields and logical operators (like 'AND' or 'OR') to narrow down records in the datastore.
Can I search for specific records inside a CSV file without downloading it? +
Yes! Use the search_datastore tool with the Resource ID. You can apply filters and limits to query the data rows directly from the portal's internal database.
How do I find all available datasets in the portal? +
Simply run the list_datasets tool. It will return a comprehensive list of dataset identifiers that you can then inspect further using get_dataset.
Can I see the categories or tags used to organize the data? +
Yes, use the list_tags tool to retrieve all the keywords and categories used by the Castilla-La Mancha portal to classify their information.
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