fetch_ifs_data
Retrieve time series data from the IMF's IFS database by specifying frequency, country, indicator, and date range for economic analysis.
Instructions
Retrieves compact format time series data from the IFS database based on the input parameters.
Args:
freq (str): Frequency (e.g., "A" for annual).
country (str): Country code, multiple country codes can be connected with "+".
indicator (str): Indicator code.
start (str | int): Start year.
end (str | int): End year.
Returns:
str: Description of the queried data. Do not perform further analysis or retry if the query fails.Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| freq | Yes | ||
| country | Yes | ||
| indicator | Yes | ||
| start | Yes | ||
| end | Yes |
Implementation Reference
- imf_data_mcp/__init__.py:69-93 (handler)The @mcp.tool() decorator registers the tool, and the function implements the core logic: constructs the IMF API URL for IFS dataset, fetches JSON data, processes it with process_imf_data helper, and returns formatted string or error.
@mcp.tool() def fetch_ifs_data(freq: str, country: str, indicator: str, start: str | int, end: str | int) -> str: """ Retrieves compact format time series data from the IFS database based on the input parameters. Args: freq (str): Frequency (e.g., "A" for annual). country (str): Country code, multiple country codes can be connected with "+". indicator (str): Indicator code. start (str | int): Start year. end (str | int): End year. Returns: str: Description of the queried data. Do not perform further analysis or retry if the query fails. """ dimensions = f"{freq}.{country}.{indicator}" url = f"http://dataservices.imf.org/REST/SDMX_JSON.svc/CompactData/IFS/{dimensions}?startPeriod={start}&endPeriod={end}" try: response = requests.get(url) response.raise_for_status() data = response.json() return process_imf_data(data) except Exception as e: return f"Error fetching IFS data: {str(e)}" - imf_data_mcp/utils.py:1-51 (helper)Helper function that parses the IMF JSON response, extracts series and observations, formats time series data into readable sentences, handles missing data warnings.
def process_imf_data(json_data: dict) -> str: """ Process IMF data and return a string with the information. :param: json_data(dict): JSON data from the IMF API :return: (str) A string with the information from the JSON data """ try: json_data = json_data["CompactData"] dataset = json_data["DataSet"] series_list = dataset["Series"] if isinstance(series_list, dict): series_list = [series_list] elif not isinstance(series_list, list): return f"Error: Expected series_list to be a list but got {type(series_list)}" output_texts = [] for series in series_list: if series is None: output_texts.append("Warning: No indicator value.") continue country = series.get("@REF_AREA", None) obs = series.get("Obs", {}) if isinstance(obs, dict): obs = [obs] elif not isinstance(obs, list): return f"Error: Expected obs to be a list but got {type(obs)}" for _obs in obs: if _obs is None: output_texts.append( f"Warning: No indicator value for {country} in that Year, You should not try to access the data of this country." ) continue time_period = _obs.get("@TIME_PERIOD", "that Year") obs_value = _obs.get("@OBS_VALUE") if obs_value is not None: text = f"In {time_period}, {country} had an indicator value of {float(obs_value):.2f}." output_texts.append(text) else: output_texts.append(f"Warning: No indicator value for {country} in {time_period}.") return "\n".join(output_texts) except KeyError as e: return f"Error processing IMF data: Missing key {str(e)}" except Exception as e: return f"Error processing IMF data: {str(e)}"