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Halpph

istat-mcp-server

by Halpph
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
MCP_DEBUGNoSet to 'true' for detailed error tracebacks in responses.false
MCP_STORAGE_DIRNoOverride the default storage directory for downloaded files.Platform-specific default (e.g., ./data on Linux/macOS)

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
get_list_of_available_datasetsA

Get a list of available datasets from ISTAT

Example:
    get_list_of_available_datasets()
search_datasetsA

Search datasets in ISTAT website by a query string

Args:
    query: The query string to search for.
    
Example:
    search_datasets(query="import")
get_dataset_dimensionsC

Get the dimensions of a dataset

Args:
    dataflow_identifier: The identifier of the dataset.

Example:
    get_dataset_dimensions(dataflow_identifier="139_176")
get_dimension_valuesC

Get the values of a dimension for a given dataset

Args:
    dataflow_identifier: The identifier of the dataset.
    dimension: The dimension to get the values for.

Example:
    get_dimension_values(dataflow_identifier="139_176", dimension="TIPO_DATO")
get_dataA
Get data from a dataset with filters. Attempt to retrieve data, if it times out or is too big,
return the URL of the file to download.

Args:
    dataflow_identifier: The identifier of the dataset.
    filters: A dictionary of filters to apply to the dataset.

Example:
    get_data(dataflow_identifier="139_176", filters={"freq": "M", "tipo_dato": ["ISAV", "ESAV"], "paese_partner": "WORLD"})
get_data_limitedA
Get limited data from a dataset with filters. Returns only the first N records.
Attempt to retrieve data, if it times out or is too big, return the URL of the file to download.

Args:
    dataflow_identifier: The identifier of the dataset.
    filters: A dictionary of filters to apply to the dataset.
    limit: The maximum number of records to return.

Example:
    get_data_limited(dataflow_identifier="139_176", filters={"freq": "M", "tipo_dato": ["ISAV", "ESAV"], "paese_partner": "WORLD"}, limit=100)
get_summaryA
Get a summary of a dataset from ISTAT.

Args:
    dataflow_identifier: The identifier of the dataset.
    filters: A dictionary of filters to apply to the dataset.
    
Example:
    get_summary(dataflow_identifier="139_176", filters={"freq": "M", "tipo_dato": ["ISAV", "ESAV"], "paese_partner": "WORLD"})
get_dataset_urlA
Get the URL to download a dataset with metadata.

Args:
    dataflow_identifier: The identifier of the dataset.
    filters: A dictionary of filters to apply to the dataset.
        Filter keys should be dimension names in lowercase.
        For unfiltered dimensions, omit them or set to None.

Example:
    get_dataset_url(dataflow_identifier="139_176", filters={"freq": "M", "tipo_dato": ["ISAV", "ESAV"], "paese_partner": "WORLD"})

Returns:
    JSON with URL and metadata (content-type, size, etc.)
download_datasetA
Download a dataset file from a URL to a local path with automatic format detection.
Better for large datasets that cannot be handled in-memory or when Json responses are too large or not supported.
The file extension is automatically determined from the Content-Type header.

Args:
    url: The URL of the file to download.
    output_path: Optional. A relative or absolute path for the saved file.
                 If relative, it's resolved against the configured storage directory.
                 If absolute, it MUST be inside the storage directory.
                 If not provided, a filename is generated from the URL with the appropriate extension.

Example:
    # Saves to <storage_dir>/my_data/export.xml (extension based on content type)
    download_dataset(url="http://.../data", output_path="my_data/export")

    # Saves to <storage_dir>/<generated_name>.<ext> (extension based on content type)
    download_dataset(url="http://.../data")

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription
istat_overviewGeneral info about ISTAT API usage.
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.7/5.0

Scored across 9 tools

Disambiguation4/5

Tools are mostly distinct: download_dataset handles file download, get_data and get_data_limited differ by limit, and others cover distinct metadata and discovery functions. Slight overlap between get_data and get_data_limited could cause confusion but descriptions clarify.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case (get_, download_, search_), making them predictable and easy to use.

Tool Count5/5

With 9 tools covering discovery, metadata, and data retrieval, the count is well-scoped for an ISTAT data access server—neither too many nor too few.

Completeness5/5

The tool set provides a complete workflow: dataset discovery (list, search), metadata exploration (dimensions, summary), and data retrieval with multiple options (filtered, limited, URL, download). No obvious gaps for its intended purpose.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources