CNMC MCP. Access Spanish market data without CSV downloads.
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CNMC (Comisión Mercados y Competencia) MCP Server gives you direct access to Spain's open data on markets and competition. Use this to search public datasets covering telecommunications, energy, transport, and postal sectors.
You can find specific resources using `package_search` and then pull actual records using `datastore_search`, all without manual downloads.
What your AI agents can do
Datastore search
Retrieves actual records (rows) from a specific CNMC resource ID found via package_search.
Package search
Searches the CNMC catalog to find resource IDs and metadata for datasets using keywords.
The package_search tool lets your agent search the entire CNMC catalog for resource IDs and metadata based on keywords.
The datastore_search tool pulls actual rows and records from a known CNMC resource ID, allowing for data extraction.
Your agent can apply structured JSON filters to limit results by date range, region, or specific category within a dataset.
The system inspects a resource's metadata, telling you its update frequency and format type before you run a query.
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CNMC (Comisión Mercados y Competencia) MCP Server: 2 Tools for Data Search
These two tools let your AI agent find specific datasets and then retrieve the actual records from the CNMC open data portal.
019e387adatastore search
Retrieves actual records (rows) from a specific CNMC resource ID found via `package_search`.
019e387apackage search
Searches the CNMC catalog to find resource IDs and metadata for datasets using keywords.
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What you can do with this MCP connector
CNMC MCP Server - Spanish Market Data Search gives your agent direct access to Spain's open data on markets and competition. You'll use this to search public datasets covering telecommunications, energy, transport, and postal sectors. First, you use package_search to search the entire CNMC catalog for resource IDs and metadata using keywords, which returns the necessary resource IDs and descriptions.
Then, you use datastore_search to pull actual rows and records from a specific resource ID, letting you extract the data you need. You can use structured JSON filters to limit results by date range, region, or specific category within a dataset. Before you run a query, the system inspects a resource's metadata, so you'll know its update frequency and format type.
This setup lets your agent find available datasets and retrieve specific data records. You'll search for available datasets using package_search to get the resource IDs and metadata. You'll retrieve specific data records using datastore_search by feeding it a known CNMC resource ID. You can apply structured JSON filters to limit results by date range, region, or specific category.
You'll check resource details to see a resource's update frequency and format type.
How CNMC MCP Works
- 1 First, use
package_searchto find the relevant dataset by querying keywords (e.g., 'gas natural') to get the necessary resource ID. - 2 Next, pass that resource ID to
datastore_search, adding any necessary JSON filters (e.g., filter by '2022') to narrow the scope. - 3 Your agent returns the requested records, which can include market shares, consumption metrics, or operational data, ready for analysis.
The bottom line is you get structured access to complex Spanish market data without downloading and cleaning CSV files.
Who Is CNMC MCP For?
Data Analysts, Legal/Compliance Teams, and Policy Researchers need this. If you spend time manually downloading, cleaning, and cross-referencing regulatory spreadsheets, this is for you. It lets you pull precise market stats directly into your workflow.
Fetches market statistics (like energy or telecom usage) by calling package_search first, then piping the results into datastore_search for immediate analysis.
Monitors regulatory changes and competition records by querying specific date ranges or sectors using JSON filters on datastore_search.
Accesses public sector information for economic modeling. They use package_search to find the correct data source, then structure queries to build reports.
What Changes When You Connect
- Stop manually downloading market reports. Use
package_searchto find the right dataset ID, then usedatastore_searchto pull the data directly into your agent's context. - Need to filter by date or region? You can apply JSON filters during the
datastore_searchcall. This lets you restrict results to, say, only Q1 2023 records, instead of processing a massive file. - The CNMC portal covers multiple sectors: energy, telecoms, transport, and postal services. Use
package_searchto narrow down the scope, so you don't have to sift through unrelated data. - The server gives you resource inspection. Before you commit to a query, your agent checks the resource's license type and update frequency, saving you time on unusable data.
- Instead of writing multi-step scripts to hit different APIs, you use two simple tools,
package_searchanddatastore_search, which keeps your agent workflow clean and focused. - Get accurate, official data. The source is the CNMC—the Spanish National Commission for Markets and Competition. This is primary regulatory data.
Real-World Use Cases
Comparing energy consumption over time
A researcher needs to compare natural gas usage between 2020 and 2022. They run package_search for 'gas natural', find the resource ID, and then call datastore_search using a JSON filter for the year 2022. The agent returns 12 monthly records, ready for a total consumption summary.
Checking market shares for a specific quarter
A compliance officer needs to see the market share data for telecom operators in Q1 2023. They use package_search to locate the relevant resource, then run datastore_search with filters for the specific date range, getting a clean table of market shares.
Finding the right dataset for a new project
A data analyst starts by running package_search with a broad query like 'energy'. The agent returns several options, allowing the analyst to pick the correct 'Estadística mensual de energía eléctrica' resource ID before proceeding to data extraction.
Modeling sector-specific economic data
A policy researcher needs transport data from 2018. They use package_search to find the transport dataset ID, and then use datastore_search with a JSON filter set to '2018' to build a historical economic model.
The Tradeoffs
Treating all data as one source
Trying to run a general search query against a single endpoint and hoping it returns all relevant market data from different sectors (energy, transport, etc.).
→
Don't assume one tool does everything. You must first use package_search to identify the precise resource ID for the sector you care about. Then, use datastore_search with that specific ID and apply targeted JSON filters.
Ignoring resource IDs
Just guessing a resource ID or trying to pull data without knowing the exact ID, leading to API failure or incomplete results.
→
The process is two steps: 1. Use package_search to find the correct resource ID. 2. Use datastore_search, passing the ID retrieved in step one. Never skip the lookup.
Over-filtering or forgetting filters
Running datastore_search on a massive dataset without specifying a date range or region, resulting in a huge data dump that overwhelms the agent and is hard to process.
→
Always use JSON filters when calling datastore_search. Limit the scope to the exact date, region, or category you need. This keeps the results small and actionable.
When It Fits, When It Doesn't
Use this MCP Server if your job requires accessing official, structured, public market data from Spain's key regulatory bodies (CNMC). You need to search by keyword and then pull records based on a specific ID and filter set. If your goal is to analyze data from a private, internal company database, this tool won't help. If you just need general industry statistics not tied to a specific Spanish regulatory body, look for a general data API wrapper instead. If you are already deep into the CNMC portal and just need to look up a resource ID, you only need package_search.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by CNMC (Comisión Mercados y Competencia). 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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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 server provides 2 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Sifting through massive, uncurated government data dumps is a massive time sink.
The old way is manually navigating the CNMC open data portal. You'd click through dozens of categories—telecom, energy, transport—to find the right resource. Then, you'd download a massive CSV file, open it in Excel, and spend hours cleaning columns, cross-referencing dates, and writing complex formulas just to get a small set of comparable metrics.
With this MCP Server, you just ask your agent. It uses `package_search` to pinpoint the exact dataset ID. Then, it uses `datastore_search` with filters to pull only the rows you need. You get the final, clean data right in your chat window. No downloads, no cleanup.
CNMC MCP Server: Search and retrieve Spanish market data.
You eliminate the need to remember specific API endpoints or juggle multiple authentication keys for different data types. The two tools, `package_search` and `datastore_search`, handle the entire lifecycle: discovery, identification, and extraction.
Now, your agent treats the CNMC portal like a single, searchable database. It's precise. It's fast. It's the data you need, nothing more.
Common Questions About CNMC MCP
How do I find the correct dataset using the CNMC MCP Server? +
Use package_search. You give it keywords like 'telecom' or 'energy', and it returns a list of potential resources and their IDs. This is your starting point.
What is the difference between `package_search` and `datastore_search`? +
package_search finds the resource ID (the dataset container). datastore_search uses that ID to pull the actual data records inside the container.
Can I filter the data by specific dates using `datastore_search`? +
Yes, you can apply JSON filters when calling datastore_search. You just specify the date range or region you want, keeping the data set small and focused.
Does the CNMC MCP Server handle multiple sectors? +
Yes. The server is built to cover multiple sectors, including telecommunications, energy, transport, and postal services. Just search for the relevant keywords.
Do I need an API key for the CNMC MCP Server? +
The documentation notes that an API Key may be required if you need higher rate limits. Check the server's setup guide for specific key requirements.
When should I use `package_search` versus `datastore_search`? +
You use package_search first. It finds the resource ID you need. Then, you pass that ID to datastore_search to actually pull the data records.
Does `datastore_search` support complex filtering for multiple fields? +
Yes, you apply JSON filters to narrow down results. You can filter by specific dates, regions, or other categories within the dataset.
What happens if my API key fails when using the CNMC MCP Server? +
The server returns a specific authentication error. You check your key and ensure it's correctly entered in the server settings to maintain access.
How do I find the resource_id needed for data retrieval? +
Use the package_search tool with a query related to your topic. The response will include a list of resources, each with a unique id (the resource_id) that you can then use in datastore_search.
Can I limit the number of records returned to avoid large payloads? +
Yes! The datastore_search tool includes an optional limit parameter. You can specify exactly how many rows you want to retrieve (e.g., 10 or 100) to keep the response concise.
Is it possible to filter data by a specific field, like a year or a city? +
Absolutely. Use the filters parameter in datastore_search. It accepts a JSON string (e.g., {"Year": "2023"}) to return only the records that match your criteria.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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