BEA MCP. Query US GDP and Income Metrics Directly
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BEA (Bureau of Economic Analysis) MCP Server connects your AI agent directly to official US economic data. Pull GDP figures, national income accounts (NIPA), and industry statistics from the source.
It lets you discover datasets, validate parameters, and retrieve raw economic figures using structured tools. Stop downloading CSVs and start querying live data.
What your AI agents can do
Get data
Fetches raw economic data from a specified BEA dataset using a JSON string of parameters.
Get dataset list
Lists all available BEA datasets, including NIPA, Regional, and GDP by Industry.
Get parameter list
Lists the required parameters (filters and variables) for a specific BEA dataset.
Runs get_dataset_list to show a list of all BEA datasets (NIPA, Regional, etc.) that your agent can access.
Runs get_parameter_list to list the specific filters and variables needed for a chosen BEA dataset.
Runs get_parameter_values to retrieve the list of valid codes for parameters like TableID or Frequency, preventing API errors.
Runs get_data to fetch raw economic figures, growth rates, and historical statistics from a defined BEA dataset.
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BEA (Bureau of Economic Analysis) MCP Server: 4 Tools
These tools allow your AI agent to discover, validate, and retrieve structured economic data from the Bureau of Economic Analysis.
019e386cget data
Fetches raw economic data from a specified BEA dataset using a JSON string of parameters.
019e386cget dataset list
Lists all available BEA datasets, including NIPA, Regional, and GDP by Industry.
019e386cget parameter list
Lists the required parameters (filters and variables) for a specific BEA dataset.
019e386cget parameter values
Provides a list of valid values for a given BEA dataset parameter, preventing query errors.
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What you can do with this MCP connector
The BEA MCP Server hooks your AI agent straight into the Bureau of Economic Analysis. You pull raw US economic data—GDP figures, national income accounts (NIPA), and industry stats—directly from the source. Forget downloading CSVs; you query live data.
get_dataset_list lists every BEA dataset your agent can access, including NIPA, Regional, and GDP by Industry. get_parameter_list then shows the specific filters and variables required for any chosen dataset. You use get_parameter_values to pull a list of valid codes for parameters like TableID or Frequency, so your agent never throws an API error.
Finally, get_data fetches the raw economic figures, growth rates, and historical statistics from a defined BEA dataset using a JSON string of parameters.
How BEA MCP Works
- 1 First, use
get_dataset_listto identify the BEA dataset you need (e.g., NIPA). - 2 Next, use
get_parameter_listandget_parameter_valuesto confirm the required parameters (like Year or Frequency) for that dataset. - 3 Finally, pass all necessary details into
get_datato retrieve the raw economic figures.
The bottom line is: the agent uses a multi-step process to validate the data structure before pulling the final numbers.
Who Is BEA MCP For?
Economists and researchers who deal with US macro data. If you spend time manually downloading, cleaning, and reconciling CSV reports from the BEA, this server saves you hours. It hands you precise, structured data directly into your analysis flow.
Integrates macroeconomic trends into market models. They use the BEA server to pull historical GDP or income data directly for forecasting.
Automates the ingestion of government-verified economic signals. They use the tools to feed structured data into machine learning pipelines.
Quickly pulls historical data—like GDP or income—without the hassle of manual API calls or downloading massive CSV files.
What Changes When You Connect
- Stop manual CSV downloads. The
get_datatool pulls raw, historical figures directly into your conversation, skipping the whole export/import step. - Avoid API errors. Use
get_parameter_valuesto check valid codes for parameters like TableID or Frequency before running a query. - Know your scope.
get_dataset_listshows every dataset available—from NIPA to International Transactions—so you never miss a data source. - Build reliable workflows. The combination of
get_parameter_listandget_parameter_valuesforces the agent to validate the query structure first, ensuring the finalget_datacall succeeds. - Analyze macro trends quickly. Financial Analysts can integrate real-time, government-verified data into forecasting models without switching context or tools.
Real-World Use Cases
Forecasting Annual GDP Growth
A financial analyst needs the real GDP for 2023. They ask their agent. The agent first runs get_dataset_list to confirm the NIPA dataset, then uses get_parameter_values to confirm 'Annual' and '2023' are valid inputs. Finally, it runs get_data to report the exact growth rate.
Checking International Trade Data
A researcher needs to compare US imports and exports. They ask their agent. The agent uses get_dataset_list to find the ITA dataset, then get_parameter_list to understand the necessary fields. It then pulls the specific international transaction figures with get_data.
Debugging a Data Query
A data scientist runs a query that fails. Instead of guessing, they use get_parameter_list on the target dataset. This shows them the required parameters, and they use get_parameter_values to confirm the correct code for 'Quarterly' instead of 'Annual'.
Gathering Comprehensive Income Data
An economist needs total personal income. They instruct their agent to check all relevant datasets. The agent uses get_dataset_list to map out NIPA and other income accounts, then executes multiple get_data calls to synthesize a full report.
The Tradeoffs
Treating the BEA API like a single query box
Trying to pass all required parameters (TableID, Frequency, Year) into get_data without first checking if the parameter values are valid. This results in an API error and no data.
→
Always run get_parameter_list first to see what fields are needed. Then, use get_parameter_values to confirm the exact valid codes for those fields before calling get_data.
Forgetting the dataset scope
Asking for 'GDP data' without specifying the source dataset ID, leading the agent to guess or fail the query entirely.
→
Start with get_dataset_list to see all available sources. Then, select the specific source (e.g., NIPA) and proceed with parameter checks.
Assuming parameter types
Inputting '2025' for a dataset that only tracks data up to 2022. The query fails, and the user has no idea why.
→
Run get_parameter_values on the target dataset's parameter. This gives you the exact list of years and frequencies the API accepts.
When It Fits, When It Doesn't
Use this server if your job requires pulling validated, structured US economic data from the BEA. You need the ability to programmatically check dataset availability (get_dataset_list) and validate parameters (get_parameter_values) before making the final data call (get_data). Don't use it if you just need general market sentiment or qualitative industry reports—those require different tools. If you only need a simple, single-point lookup without validation steps, you might be over-engineering; however, for reliable, production-grade data, this multi-step approach is necessary.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by BEA (Bureau of Economic Analysis). 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 4 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Manual data gathering requires jumping between multiple government websites and downloading massive, confusing CSV files.
Today, getting a full picture of the US economy means navigating the BEA website. You click into the NIPA tables, then download a CSV. If you need a different variable, you open a new tab, search for the new table ID, and download another file. You spend hours just reconciling these separate spreadsheets.
With the BEA MCP Server, your agent does the heavy lifting. You tell it what you need—say, 'Real GDP for 2023.' The agent uses `get_dataset_list` and `get_parameter_list` to find the right table, validates the parameters, and runs `get_data` to give you the single, clean number you need.
BEA MCP Server: Get Verified Macro Data in Minutes
The time sink of manual data reconciliation—the copying of Table IDs, the switching of tabs, the formatting of headers—vanishes. You don't build the query; the agent builds it using the `get_parameter_list` and `get_parameter_values` tools.
The difference now is control. You stop dealing with files and start dealing with data points. This process is immediate and auditable.
Common Questions About BEA MCP
How do I start querying with the BEA (Bureau of Economic Analysis) MCP Server? +
You start by asking your agent to list the available datasets. The agent runs get_dataset_list to show you all the sources (NIPA, etc.) you can query.
What is the difference between `get_parameter_list` and `get_parameter_values`? +
get_parameter_list shows you what filters a dataset accepts (e.g., Year, Frequency). get_parameter_values shows you the actual valid options for those filters (e.g., A, Q, or 2023).
Can I get historical data for any dataset using the BEA (Bureau of Economic Analysis) MCP Server? +
Yes. After identifying the dataset and validating the parameters, you use get_data to pull historical figures and growth rates directly.
Do I need to provide an API key to use the BEA (Bureau of Economic Analysis) MCP Server? +
Yes. You must subscribe and enter your BEA API Key for the server to connect to the source data.
How does `get_dataset_list` help me find what economic data is available? +
It lists all datasets available from the BEA. This function returns dataset names like NIPA and FixedAssets, letting you know exactly what kind of economic data you can query.
What parameters must I use when calling `get_data`? +
You must provide parameters like 'TableID' and 'Year' in a JSON string. The specific requirements depend on the dataset you select, so always check the parameter list first.
If I get an error querying data, how can `get_parameter_values` help me fix it? +
It provides lists of valid codes for parameters like Frequency or TableID. If your query fails due to an invalid code, checking the valid values prevents the API error.
Does the BEA MCP Server handle different types of economic data, like GDP and income? +
Yes, it covers major US economic indicators, including GDP and personal income. You can retrieve historical figures and growth rates across these core datasets.
How can I see which economic datasets are available? +
You can use the get_dataset_list tool. It will return a comprehensive list of all datasets currently supported by the BEA API, such as NIPA, NIUnderlyingDetail, and FixedAssets.
How do I know what filters or parameters to use for a specific dataset? +
First, use get_parameter_list with the dataset name to see required fields. Then, use get_parameter_values to find valid inputs (like specific Year or TableID) for those parameters.
Can I fetch actual GDP or income figures directly? +
Yes. Use the get_data tool. You will need to provide the dataset name and a JSON string of parameters (e.g., TableName, Frequency, Year) to retrieve the specific economic observations.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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