Murcia Data MCP for AI. Query regional statistics and data catalogs via API calls.

Q: How do I search for data on a specific topic using searchdatasets?

searchdatasets takes a keyword (like 'medio ambiente') and returns all matching datasets. It's much better than browsing because you don't have to guess which category the data lives in.

Q: Do I need listorganizations before I can search for anything?

No, but it helps define your scope. You can run searchdatasets immediately. However, if you want to limit results only to the 'Health Department,' running listorganizations first and passing that name to the agent gives you better control.

Q: What's the difference between listgroups and searchdatasets?

listgroups only shows the official, high-level categories (like 'Environment'). searchdatasets, however, lets you use specific keywords ('calidad del aire') to find data that might not fit into a standard group.

Q: How do I check if a dataset is current using getmostrecentdatasets?

getmostrecentdatasets shows the metadata for datasets that were recently added to the catalog. This tells you about new information, not necessarily data that was just updated.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Connect to your AI in seconds.

Región de Murcia Datos Abiertos connects your AI client directly to the official open data catalog for the Region of Murcia, Spain.

It lets you programmatically query thousands of public datasets, list all contributing government organizations, and search specific regional statistics (like environment or demographics) without navigating a web portal.

What your AI can do

Get dataset

Retrieves all metadata and details for a specific dataset ID.

Get most recent datasets

Lists datasets that were most recently added to the catalog.

Get most viewed datasets

Identifies and lists the datasets that have been viewed or accessed most frequently.

+ 4 more capabilities included

Search for specific data sets

Find datasets using keywords or filters via the search_datasets tool.

Browse by publishing organization

List all government departments and organizations that contribute data through list_organizations.

Explore data categories

View the full list of predefined subject groups using the list_groups tool.

Check dataset metadata

Pull complete details—formats, descriptions, links—for a single dataset with get_dataset.

Identify data trends

Determine popular or newly added datasets by calling get_most_viewed_datasets or get_most_recent_datasets.

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AI Agent

Región de Murcia Datos Abiertos MCP Server: 7 Tools for Data Discovery

These seven tools let your agent navigate the entire open data catalog. You can discover datasets by searching keywords, listing organizations, and checking trends.

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 Región de Murcia Datos Abiertos on Vinkius

Get Dataset

Retrieves all metadata and details for a specific dataset ID.

Get Most Recent Datasets

Lists datasets that were most recently added to the catalog.

Get Most Viewed Datasets

Identifies and lists the datasets that have been viewed or accessed most frequently.

List Datasets

Outputs a list of every single dataset currently available in the entire catalog.

List Groups

Retrieves all predefined subject groups or categories within the data portal.

List Organizations

Lists every government organization or group that publishes data on the site.

Search Datasets

Searches the entire catalog for datasets matching specific keywords or criteria.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

Start a conversation

Open a new chat. The Murcia Data integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "region-de-murcia-datos-abiertos": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the Murcia Data tools with full Vinkius guardrails applied.

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"region-de-murcia-datos-abiertos": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

Import from OpenAPI, Swagger, or YAML specs
Create Agent Skills with progressive disclosure
Deploy to edge with MCPFusion framework
Built in DLP, auth, and compliance on every call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with Región de Murcia Datos Abiertos, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,100+ others, all in one place
Add new capabilities to your AI anytime you want
Every connection is secured and compliant automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog every week

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Región de Murcia Datos Abiertos. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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V8 Isolated

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No stored credentials

DLP Enforced

Policy on every call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

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 7 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Figuring out which agency has the data is the hardest part of open data.

Today, finding public stats for something like regional economy means clicking through multiple departmental websites. You check the environment portal, then the city hall site, then maybe a different government body's page—each with its own confusing menu structure and inconsistent naming conventions. Copying links is a nightmare.

With this MCP server, you ask your agent to find data on regional economy. The system runs `list_organizations` first, giving you a clean list of potential contributors. Then it uses `search_datasets` across all of them. You get the right dataset name and its metadata back instantly. No manual clicking needed.

Using the Región de Murcia Datos Abiertos MCP Server: 7 Tools for Discovery

Manual research requires checking five different places just to see what's new or most popular. You check the 'new stuff' tab, then the 'popular' list, and then you have to manually remember which department published it all in the first place.

Now, your agent handles this: It can run `get_most_recent_datasets` *and* `list_organizations` simultaneously. You get a single, structured answer that tells you both what was added today and who put it there. The process is faster, cleaner, and more reliable.

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What your AI can actually do with this

You connect your AI client straight into the official open data catalog for the Region of Murcia. This server gives you direct access to thousands of public datasets, letting you query regional stats—everything from environment reports and local economies to population figures—without having to mess around on a web portal.

Discovery: Finding What You Need

If you're starting from scratch and just need an overview, you can run list_datasets to pull a complete inventory of every single dataset available in the entire catalog. For targeted research, don't worry about manually browsing; you use search_datasets to search the whole collection using keywords or specific criteria. You want to narrow down the scope? Run list_groups, and you get all the predefined subject groups—the main categories for data like 'Health' or 'Transportation.' To focus on who published it, run list_organizations; this spits out a list of every government department or group that contributes data to the site.

You can combine these tools: first check list_groups for broad topics, then use those keywords in search_datasets.

Trend Tracking and Dataset Status

You're trying to figure out what people are actually looking at? Run get_most_viewed_datasets, and you instantly get the list of datasets that have been accessed most frequently. Need to know what’s fresh? You call get_most_recent_datasets to pull a roster of everything that was just added to the catalog. These tools let you track data interest, showing you what's popular or what's brand new.

Deep Dive Metadata Retrieval

Once you zero in on a specific ID, you don't want guesswork. You need complete details—formats, descriptions, resource links—right away. That’s where get_dataset comes in. If you feed it a single dataset ID, you get all the metadata and full specifications for that one entry. It's like pulling up the detailed spec sheet on your phone.

How Your Agent Uses This:

Your AI client executes these functions directly. You don't build web forms or click through menus. When your agent runs search_datasets(query='urban development'), for example, the server doesn't just give you a link; it returns structured JSON metadata describing all relevant datasets, who created them, and exactly where they live in the catalog.

If you run list_organizations, your agent gets back every contributing body. If you follow that up by calling get_dataset(id='...') for a specific dataset from one of those organizations, you get the complete picture: the origin, the full description, and whether it's formatted as CSV or JSON.

This server lets your agent do everything from listing all available datasets with list_datasets, to finding the top-tier data using get_most_viewed_datasets, all while keeping the output clean and machine-readable. You're always working off structured JSON, period. You can run search_datasets for keywords, then use list_groups to refine those keywords into categories, giving you a layered approach that traditional web browsing just can't match.

Built · Hosted · Managed by Vinkius Murcia Open Data MCP Server - Query Regional Datasets

Server ID 019e38e2-be77-713d-a223-8e47dd038328

Vinkius Inspector

Compliance Grade A+

Score 100/100

Report View Report ↗

Here's how it actually works

The bottom line is that your AI client handles all the API calls; you just talk to it in natural language.

Subscribe to the server and (if needed) provide your Murcia API Key.

Tell your AI agent exactly what data you need. For example, 'Search for environment datasets published by the health service.'

The agent uses tools like list_organizations, then search_datasets, and finally get_dataset to return structured metadata.

Who is this actually for?

This server is for anyone who needs to gather public, structured regional data without manually clicking through a government website. If you're tired of spending hours navigating open-data portals or copying URLs, this is for you.

Data Analyst

Needs to quickly pull statistics on demographics or infrastructure by calling search_datasets and filtering results.

Academic Researcher

Requires bulk metadata for multiple datasets related to a specific field (e.g., 'medio ambiente') using list_groups.

Backend Developer

Needs to embed real-time data discovery into an application, calling tools like get_dataset programmatically.

What Changes When You Connect

Structured discovery: Instead of browsing, you call search_datasets to filter results by keyword. It's instant and precise.

Source mapping: Use list_organizations to get a clear inventory of every department contributing data—you know exactly who owns the stats.

Trend awareness: Know what’s hot or new with get_most_viewed_datasets and get_most_recent_datasets. Don't waste time looking at stale info.

Deep inspection: When you find a promising dataset, get_dataset gives you all the technical details—formats, resource links, everything—in one call.

Systematic browsing: Need to scope your search? Use list_groups first. It lets you walk through the data catalog by official subject area.

See it in action

01 01

Mapping all contributing agencies

You need a list of every agency that reports on public health in Murcia for a report. Instead of clicking deep into multiple sections, you simply ask the agent to use list_organizations. The result is an immediate, structured JSON list of contributors.

02 02

Finding environmental data quickly

A student needs statistics on air quality ('calidad del aire'). They don't know which department has the data. Asking the agent to search_datasets for 'medio ambiente' instantly narrows down thousands of results to relevant, actionable datasets.

03 03

Building a dashboard feature

A developer needs to show users the most popular local government spending figures. They call get_most_viewed_datasets, get the names like 'Presupuestos Municipales', and build their component around that structured list.

04 04

Tracking data updates

The team needs to know what new economic metrics were added this week. Instead of checking multiple departmental portals, they call get_most_recent_datasets to see only the latest additions across the entire region's catalog.

The honest tradeoffs

Using `list_groups` for a specific topic

Anti-pattern

A user thinks that running list_groups will show them all datasets about 'water usage'. It only shows the high-level categories (e.g., Health, Economy), forcing them to guess which group contains the data.

The Fix

Don't use list_groups. You need to pinpoint the topic directly. Use search_datasets(query='uso de agua') instead; that function actually searches the metadata for you.

Assuming popularity equals value

Anti-pattern

A user only calls get_most_viewed_datasets and assumes those are the most relevant datasets, missing out on critical new information.

The Fix

Always check both ends of the spectrum. Run get_most_viewed_datasets to see what's established, but also run get_most_recent_datasets for fresh insights.

Forgetting dataset specifics

Anti-pattern

After searching and finding a relevant record name, the user stops there. They don't know if the data is clean, or what format it comes in.

The Fix

Never trust just the title. After any successful search or list function, call get_dataset using the ID to verify the full metadata, formats, and required resource links.

When It Fits, When It Doesn't

Use this server if your goal is data discovery: you need a structured map of available data sets—who published them, what topics they cover, or which ones are most popular. The tools like list_organizations, search_datasets, and get_dataset make it an excellent metadata catalog client.

Don't use this if your goal is data querying or transformation. This server gives you the pointers to data, not the actual cleaned tables. If you need to calculate a metric (e.g., 'What was the population growth between 2018 and 2023?'), you still have to retrieve the raw resource links from get_dataset and run that logic in your own application or agent pipeline. It's a lookup tool, not an analysis engine.

Questions you might have

How do I search for data on a specific topic using `search_datasets`? +

search_datasets takes a keyword (like 'medio ambiente') and returns all matching datasets. It's much better than browsing because you don't have to guess which category the data lives in.

Do I need `list_organizations` before I can search for anything? +

No, but it helps define your scope. You can run search_datasets immediately. However, if you want to limit results only to the 'Health Department,' running list_organizations first and passing that name to the agent gives you better control.

What's the difference between `list_groups` and `search_datasets`? +

list_groups only shows the official, high-level categories (like 'Environment'). search_datasets, however, lets you use specific keywords ('calidad del aire') to find data that might not fit into a standard group.

How do I check if a dataset is current using `get_most_recent_datasets`? +

get_most_recent_datasets shows the metadata for datasets that were recently added to the catalog. This tells you about new information, not necessarily data that was just updated.

If I exceed my API quota while running `get_dataset`, what happens? +

The system returns an HTTP 429 error. This means you hit the rate limit for the specified timeframe, and you need to wait before retrying the call. Using the dedicated Murcia API Key helps manage these limits.

Does `get_dataset` provide enough detail to know if I can download the data? +

Yes, it retrieves comprehensive metadata, including the required file format and direct resource links for the dataset. You'll find all the necessary paths there.

When I use `list_datasets`, what kind of domain information do I get for each entry? +

It returns a list containing basic identifiers, titles, and general subject categories. This helps you quickly gauge if the dataset falls within your desired field like environment or economy.

Can `search_datasets` filter results by a specific group name for better accuracy? +

Yes, passing the organization's identifier during the search narrows down results significantly. This is much more precise than simply searching keywords across all available datasets.

How can I find datasets related to a specific topic like 'transport'? +

You can use the search_datasets tool. Just provide a query string like 'transporte' and the agent will return all matching packages from the Murcia portal.

Can I see which public data is currently trending or most popular? +

Yes! Use the get_most_viewed_datasets tool to retrieve the ten most visited datasets in the portal, or get_most_recent_datasets for the latest additions.

How do I get the full details and download links for a specific dataset? +

Use the get_dataset tool with the dataset's ID or name. It will provide complete metadata, including descriptions of the resources and their access URLs.

Connect to your AI in seconds.

Get dataset

Get most recent datasets

Get most viewed datasets

Región de Murcia Datos Abiertos MCP Server: 7 Tools for Data Discovery

Make your AI actually useful.

Get Dataset

Get Most Recent Datasets

Get Most Viewed Datasets

List Datasets

List Groups

List Organizations

Search Datasets

Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

Works with Claude, ChatGPT, Cursor, and more

Figuring out which agency has the data is the hardest part of open data.

Using the Región de Murcia Datos Abiertos MCP Server: 7 Tools for Discovery

What your AI can actually do with this

Here's how it actually works

Who is this actually for?

What Changes When You Connect

See it in action

Mapping all contributing agencies

Finding environmental data quickly

Building a dashboard feature

Tracking data updates

The honest tradeoffs

Using `list_groups` for a specific topic

Assuming popularity equals value

Forgetting dataset specifics

When It Fits, When It Doesn't

Questions you might have