Knoema MCP. Fetch global statistics and time-series data.
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Knoema gives your AI agent access to global statistics. Search millions of datasets, retrieve specific time-series data (like GDP or CPI), and audit economic indicators from sources like the IMF and World Bank.
You can list available topics, units, and data frequencies, or search for specific indicators across providers. It's the data backbone for economic and academic research.
What your AI agents can do
Get data series
Retrieves specific time-series data points when you provide a dataset ID and a list of indicator mnemonics.
Get dataset metadata
Gets detailed information about a dataset, including available variables and units.
Get knoema resource
Fetches a generic resource from the Knoema platform.
You find specific indicators (like 'Crude Oil Price') regardless of which dataset they belong to, using the search_data_series tool.
You search for dataset IDs and names using search_datasets to find the correct source for your statistics.
You fetch actual historical data points by providing a dataset ID and a list of indicator mnemonics using get_data_series.
You list available topics, units, or data frequencies using tools like list_data_topics or list_data_units to confirm scope.
You get the most recent data points for any dataset using get_latest_dataset_data.
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Supported MCP Clients
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019d75c2get data series
Retrieves specific time-series data points when you provide a dataset ID and a list of indicator mnemonics.
019d75c2get dataset metadata
Gets detailed information about a dataset, including available variables and units.
019d75c2get knoema resource
Fetches a generic resource from the Knoema platform.
019d75c2get latest dataset data
Pulls the most recent data points available for any given dataset.
019d75c2list data frequencies
Lists the types of data periods available, such as Annual, Quarterly, or Monthly.
019d75c2list data topics
Lists all available high-level data subjects, such as Agriculture or Demographics.
019d75c2list data units
Lists the measurement units used across the platform, like Percentage or USD.
019d75c2list dataset regions
Lists the specific geographical regions supported by a particular dataset.
019d75c2search data series
Finds specific indicators (like 'GDP') across all datasets, which is better than searching by dataset name.
019d75c2search datasets
Searches the entire Knoema library to find relevant datasets by name and topic.
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What you can do with this MCP connector
Knoema MCP Server
Your AI client gets direct access to global statistics. Instead of searching Google for datasets, you get precise, auditable numbers. You can ask your agent to pull data right into your chat.
Search Indicators Across All Data
To find a specific metric, like 'Crude Oil Price,' you use search_data_series. This tool finds the indicator across all datasets, so you don't have to know which dataset holds the number you need. Need to find the right source? You use search_datasets to search the entire Knoema library by name or topic.
Checking Data Scope
Before pulling numbers, you can check the scope of the data. list_data_topics shows you every high-level subject, like Agriculture or Demographics. You can check the measurement units with list_data_units, which lists everything from Percentage to USD. You know what time periods are available by calling list_data_frequencies, which lists types like Annual, Quarterly, or Monthly.
To see which regions a dataset covers, you use list_dataset_regions on a specific dataset.
Retrieving Data
When you're ready for the numbers, you use get_data_series to pull actual historical data points. You just gotta give it a dataset ID and a list of indicator mnemonics, and it pulls the time-series data. For the most current snapshot, get_latest_dataset_data pulls the most recent data points available for any dataset.
You can get deep details on any dataset using get_dataset_metadata, which shows you available variables and units.
General Access
search_data_series finds metrics like 'GDP' no matter where they live. search_datasets lets you pinpoint the right source using names and topics. get_data_series fetches historical time-series data with a dataset ID and indicator mnemonics. get_latest_dataset_data grabs the newest available data for any dataset. list_data_topics lists all available high-level data subjects. list_data_units lists all measurement units. list_data_frequencies lists data periods like Annual or Quarterly. list_dataset_regions lists specific geographical regions for a dataset. get_dataset_metadata gives detailed info on a dataset, including its variables and units. get_knoema_resource fetches a generic resource from the Knoema platform.
How Knoema MCP Works
- 1 Subscribe to the server and input your Knoema Client ID and Secret into your AI client.
- 2 Ask your agent for the data you need. For example: 'What was the GDP growth in China in 2010?'
- 3 The agent calls
search_data_seriesorsearch_datasetsto find the source, then usesget_data_seriesto pull the actual numbers.
The bottom line is that your agent handles the complex search and retrieval logic, letting you talk to global statistics like they're in a database.
Who Is Knoema MCP For?
The market researcher who needs historical CPI data for a competitive analysis. The academic writing a literature review on global warming trends. The financial analyst building a macro-economic model. Anyone whose job depends on accurate, cross-border statistics.
Uses search_data_series to find comparable market indicators across different countries and time periods.
Uses get_data_series to pull time-series data for forecasting or scenario modeling.
Uses get_dataset_metadata to validate the source, units, and frequency of data before running any analysis.
What Changes When You Connect
- Need to compare inflation rates across ten countries? Use
search_data_seriesto find the common indicator across multiple providers, instead of checking ten separate dashboards. - Don't waste time downloading data.
get_data_seriestakes a dataset ID and a list of mnemonics, and your agent pulls the exact time-series numbers you need, right into your chat. - Validate your data source. Before building a model, call
get_dataset_metadatato confirm the dataset's units, scope, and variables. This saves hours of cleaning. - Scope your search with
list_data_topicsorlist_data_units. If you're unsure what data is available, these tools give you a checklist of everything Knoema tracks. - Get an instant data check with
get_latest_dataset_data. You need to know the current CPI for a region? This tool gives you the most recent data points immediately.
Real-World Use Cases
Modeling a Global Market Trend
A financial analyst needs to track how the price of crude oil relates to global GDP. They ask their agent to search for both 'Crude Oil Price' and 'GDP' using search_data_series. The agent retrieves the time-series data using get_data_series, allowing the analyst to build a comparative model without manual data export.
Academic Research on Resource Allocation
A PhD student needs environmental data for a paper comparing renewable energy capacity across Europe. They use search_datasets to locate relevant sources (e.g., 'Eurostat: Energy statistics'), then use list_dataset_regions to ensure the dataset covers all necessary geographical areas.
Business Planning for Emerging Markets
A consultant needs demographic data for a new market entry plan. They first use list_data_topics to narrow the scope to 'Demographics' and then use search_datasets to find specific source data on population growth for targeted regions.
Auditing Historical Economic Data
A risk manager needs to verify the historical unit of measure for a key indicator. They call get_dataset_metadata on the dataset ID to confirm if the unit is USD, Percentage, or something else, preventing calculation errors.
The Tradeoffs
Treating it like a simple keyword search
Asking the agent, 'Show me all data on energy.' This is too vague and won't generate a specific data call.
→
Be specific about the indicator and the scope. First, run list_data_topics to narrow it to 'Energy,' then use search_data_series to find the exact indicator name, and finally ask the agent to retrieve the data.
Assuming data is available everywhere
Asking the agent to pull a series that might not exist for a specific country or year, leading to a failed retrieval.
→
Always check availability first. Use list_dataset_regions to confirm the dataset supports your country, or use list_data_frequencies to confirm the required time granularity.
Copying data manually from a webpage
A user manually navigates to Knoema, copies a table, and pastes it into the chat, losing the source metadata and context.
→
Let your agent handle it. Use search_data_series to identify the indicator, and let the agent execute get_data_series to pull the clean, structured data directly into your conversation.
When It Fits, When It Doesn't
Use Knoema if your core task requires structured, historical, or global economic data (e.g., GDP, CPI, oil prices). Don't use it if you just need a simple list of concepts or recent news headlines—that's a general search engine job. You need to know which tool to start with: If you know the indicator name, use search_data_series. If you know the source name, use search_datasets. If you need to check the data's rules, use get_dataset_metadata. If you need the numbers, use get_data_series. If you're lost, start with list_data_topics to orient yourself.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Knoema. 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 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Sifting through global statistics used to be a nightmare of tabs and downloads.
Today, getting a full picture of, say, the CPI change across multiple countries means opening a browser, navigating to the data source, finding the right indicators, and manually exporting CSVs for every country and every year. You end up with a dozen files to stitch together in Excel, losing track of which source was which.
With Knoema, you just ask your agent. It finds the indicator, handles the data retrieval, and delivers the complete, structured time-series data right in your chat. The whole process stays contained, and the data is ready for immediate analysis.
Knoema MCP Server: Structured Data Retrieval
You skip the entire manual process of searching multiple vendor sites, dealing with inconsistent data formats, and reconciling differing time periods. The agent orchestrates the search, pulls the metadata, and retrieves the data points in one go.
It's not just about getting data; it's about knowing the source, the unit, and the frequency for every number you see. That's the difference.
Common Questions About Knoema MCP
How do I use the `search_data_series` tool with Knoema MCP Server? +
The search_data_series tool finds specific indicators across all datasets. You pass the indicator name (like 'GDP') to this tool, and it returns a list of matching series and their source IDs.
What is the difference between `search_datasets` and `search_data_series`? +
search_datasets finds entire data sources (e.g., 'IMF World Economic Outlook'). search_data_series finds specific indicators (e.g., 'Inflation Rate') regardless of which dataset they belong to.
Can I use `get_dataset_metadata` to check data rules? +
Yes. get_dataset_metadata provides detailed information on a dataset's variables, units, and expected variables. It's critical for validating what data is actually available.
How does `get_data_series` work? +
get_data_series pulls the actual historical data. It requires two key inputs: the specific dataset ID and a list of indicator mnemonics.
What is the purpose of the `list_data_topics` tool? +
It lists all available data categories in Knoema. You run this first to see topics like 'Economy' or 'Agriculture', which helps narrow your search before using search_data_series.
How do I find available measurement units using `list_data_units`? +
The list_data_units tool provides a list of standard measurements, such as 'Percentage' or 'USD'. Knowing this prevents errors when specifying metrics in get_data_series.
What should I check before running `get_dataset_metadata`? +
You should check the dataset ID first. This tool requires the specific ID to fetch detailed information about the variables, units, and time spans available in that particular dataset.
Does `get_latest_dataset_data` give historical records? +
No, get_latest_dataset_data only fetches the most recent data point. If you need a time-series of historical records, you must use the get_data_series tool.
Where do I get my Knoema API credentials? +
Visit the Knoema Developer Portal (knoema.com/dev), create an application, and you will receive a Client ID and Client Secret.
How can I find a specific dataset ID? +
Use the search_datasets tool with relevant keywords. The tool will return a list of matching datasets along with their unique IDs.
What is a mnemonic in Knoema? +
A mnemonic is a short, human-readable code used to identify a specific data series within a dataset (e.g., 'NGDP' for Nominal GDP).
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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