This MCP server provides seamless access to Malaysia's government open data, including datasets, w…
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
datagovmy_filter_datasets_catalogue1 field changedInput schema / properties / yearRange / itemsPrevious value: -[
- {
- "type": "number"
- },
- {
- "type": "number"
- }
-]New value: +{
+ "type": "number"
+}datagovmy_parse_parquet_file8 fields changedInput schema / properties / columnsAdded value: +{
+ "description": "List of column names to include. Omit to include all columns. Reduces response size and speeds up parsing.",
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+}Input schema / properties / filter_columnAdded value: +{
+ "description": "Column name to filter on (exact match). Use with filter_value.",
+ "type": "string"
+}Input schema / properties / filter_date_fromAdded value: +{
+ "description": "Start date (inclusive) for date range filtering, e.g. \"2025-01-01\" or \"2025\". Auto-detects the date column.",
+ "type": "string"
+}Input schema / properties / filter_date_toAdded value: +{
+ "description": "End date (inclusive) for date range filtering, e.g. \"2025-12-31\" or \"2025\". Auto-detects the date column.",
+ "type": "string"
+}Input schema / properties / filter_valueAdded value: +{
+ "description": "Value to match in filter_column (exact string match).",
+ "type": "string"
+}Input schema / properties / group_byAdded value: +{
+ "description": "Column to group by (summary mode only). Returns aggregated numeric stats per group.",
+ "type": "string"
+}Input schema / properties / maxRows / descriptionPrevious value: -"Maximum number of rows to return (1-2000)"New value: +"Maximum number of rows to return or sample for statistics (default 500)"Input schema / properties / output_modeAdded value: +{
+ "description": "Output format. \"raw\" (default) returns full row data. \"summary\" returns column statistics and sample rows for AI consumption. \"latest\" returns only the most recent time period.",
+ "enum": [
+ "raw",
+ "summary",
+ "latest"
+ ],
+ "type": "string"
+}datagovmy_filter_datasets_cataloguedatagovmy_find_dashboard_for_parquetdatagovmy_find_nearest_transit_stopsdatagovmy_get_dashboard_chartsdatagovmy_get_dashboard_detailsdatagovmy_get_dataset_detailsdatagovmy_get_dataset_filtersdatagovmy_get_dosm_datasetdatagovmy_get_earthquake_warningsdatagovmy_get_flood_warningsdatagovmy_get_gtfs_realtime_vehicle_positiondatagovmy_get_gtfs_staticdatagovmy_get_parquet_infodatagovmy_get_transit_arrivalsdatagovmy_get_transit_routesdatagovmy_get_transit_stopsdatagovmy_get_transport_datadatagovmy_get_weather_forecastdatagovmy_get_weather_warningsdatagovmy_hellodatagovmy_list_dashboardsdatagovmy_list_datasets_cataloguedatagovmy_list_dosm_datasetsdatagovmy_list_transport_agenciesdatagovmy_parse_gtfs_realtimedatagovmy_parse_gtfs_staticdatagovmy_parse_parquet_filedatagovmy_search_alldatagovmy_search_dashboardsdatagovmy_search_datasets_cataloguedatagovmy_search_transit_stops_by_locationClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
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There is significant overlap between tools, especially in search and transit functions, which could cause confusion. For example, search_all, search_dashboards, and search_datasets_catalogue have overlapping purposes, and tools like get_transit_routes and parse_gtfs_static serve similar functions. However, descriptions provide some guidance to differentiate them.
All tool names follow a consistent snake_case pattern with a 'datagovmy_' prefix and descriptive verb_noun combinations. The naming is highly predictable and uniform across all 31 tools, making it easy to understand their purposes at a glance.
With 31 tools, the count feels excessive for the domain of Malaysian open data access. Many tools could be consolidated, such as the multiple search and transit-related tools, leading to a bloated interface that may overwhelm agents and increase misselection risk.
The tool set covers a wide range of data types, including datasets, dashboards, transit, weather, and warnings, with good CRUD-like operations for filtering and retrieving data. Minor gaps exist, such as limited update or delete capabilities, but these are typical for read-heavy data platforms, and agents can work around them effectively.