by hithereiamaliff
Discover Malaysia Open Data: AI-first access, intelligent search, and seamless integration for Malaysia's leading open d
Provides AI-friendly access to Malaysia's government open datasets through unified search, data parsing, and geocoding capabilities. Connects to official Malaysian government data sources including statistics, weather, and transport data.
Malaysia Open Data is a community-built MCP server published by hithereiamaliff that provides AI assistants with tools and capabilities via the Model Context Protocol. Discover Malaysia Open Data: AI-first access, intelligent search, and seamless integration for Malaysia's leading open d It is categorized under analytics data.
You can install Malaysia Open Data in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Malaysia Open Data is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
We evaluated Malaysia Open Data against two servers with overlapping tools; this profile had the clearer scope statement.
We wired Malaysia Open Data into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Malaysia Open Data is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Malaysia Open Data is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Malaysia Open Data reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Malaysia Open Data is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Malaysia Open Data reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
I recommend Malaysia Open Data for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Strong directory entry: Malaysia Open Data surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We evaluated Malaysia Open Data against two servers with overlapping tools; this profile had the clearer scope statement.
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MCP Endpoint: https://mcp.techmavie.digital/datagovmy/mcp
Analytics Dashboard: https://mcp.techmavie.digital/datagovmy/analytics/dashboard
MCP (Model Context Protocol) server for Malaysia's Open Data APIs, providing easy access to government datasets and collections.
Do note that this is NOT an official MCP server by the Government of Malaysia or anyone from Malaysia's Open Data/Jabatan Digital Negara/Ministry of Digital team.
This MCP server fetches dataset and dashboard metadata live from the data-gov-my/datagovmy-meta GitHub repository:
This approach provides several benefits:
When integrating this MCP server with AI models:
search_all for any data querieshttps://data.gov.my/... and https://open.dosm.gov.my/...parse_parquet_file to access data directly or get_parquet_info for metadatafind_dashboard_for_parquetRefer to PROMPT.md for comprehensive AI integration guidelines.
npm install
The easiest way to use this MCP server is via the hosted endpoint. No installation required!
Server URL:
https://mcp.techmavie.digital/datagovmy/mcp
You can provide your own API keys via URL query parameters:
https://mcp.techmavie.digital/datagovmy/mcp?googleMapsApiKey=YOUR_KEY
Or via headers:
X-Google-Maps-Api-Key: YOUR_KEYX-GrabMaps-Api-Key: YOUR_KEYX-AWS-Access-Key-Id: YOUR_KEYX-AWS-Secret-Access-Key: YOUR_KEYX-AWS-Region: ap-southeast-5Supported Query Parameters:
| Parameter | Description |
|---|---|
googleMapsApiKey | Google Maps API key for geocoding |
grabMapsApiKey | GrabMaps API key for Southeast Asia geocoding |
awsAccessKeyId | AWS Access Key ID for AWS Location Service |
awsSecretAccessKey | AWS Secret Access Key |
awsRegion | AWS Region (default: ap-southeast-5) |
⚠️ Important: GrabMaps Requirements
To use GrabMaps geocoding, you need ALL FOUR parameters:
grabMapsApiKeyawsAccessKeyIdawsSecretAccessKeyawsRegionGrabMaps uses AWS Location Service under the hood, so AWS credentials are required alongside the GrabMaps API key.
For Claude Desktop / Cursor / Windsurf, add to your MCP configuration:
{
"mcpServers": {
"malaysia-opendata": {
"transport": "streamable-http",
"url": "https://mcp.techmavie.digital/datagovmy/mcp"
}
}
}
With your own API key:
{
"mcpServers": {
"malaysia-opendata": {
"transport": "streamable-http",
"url": "https://mcp.techmavie.digital/datagovmy/mcp?googleMapsApiKey=YOUR_KEY"
}
}
}
If you prefer to run your own instance, see deploy/DEPLOYMENT.md for detailed VPS deployment instructions with Docker and Nginx.
The hosted server includes a built-in analytics dashboard:
Dashboard URL: https://mcp.techmavie.digital/datagovmy/analytics/dashboard
| Endpoint | Description |
|---|---|
/analytics | Full analytics summary (JSON) |
/analytics/tools | Detailed tool usage stats (JSON) |
/analytics/dashboard | Visual dashboard with charts (HTML) |
The dashboard tracks:
Auto-refreshes every 30 seconds.
search_all: Primary search tool — searches across both datasets and dashboards with intelligent fallback and scoringlist_datasets_catalogue: Lists available datasets in the Data Cataloguesearch_datasets_catalogue: Searches datasets in the Data Cataloguefilter_datasets_catalogue: Filters datasets by frequency, geography, demography, data source, or year rangeget_dataset_details: Gets metadata/details for a specific datasetget_dataset_filters: Gets available filter options for datasetslist_dashboards: Lists all available dashboardssearch_dashboards: Searches dashboards by queryget_dashboard_details: Gets comprehensive metadata for a dashboardget_dashboard_charts: Gets chart configurations for a specific dashboardlist_dosm_datasets: Lists available datasets from DOSMget_dosm_dataset: Gets data from a specific DOSM datasetparse_parquet_file: Parse and display data from a Parquet file URL
get_parquet_info: Get metadata and structure information about a Parquet filefind_dashboard_for_parquet: Find the corresponding dashboard URL for a Parquet fileget_weather_forecast: Gets weather forecast for Malaysiaget_weather_warnings: Gets current weather warnings for Malaysiaget_earthquake_warnings: Gets earthquake warnings for Malaysialist_transport_agencies: Lists available transport agencies with GTFS dataget_transport_data: Gets GTFS data for a specific transport agencyparse_gtfs_static: Parses GTFS Static data (ZIP files with CSV data) for a specific transport providerparse_gtfs_realtime: Parses GTFS Realtime data (Protocol Buffer format) for vehicle positionsget_transit_routes: Extracts route information from GTFS dataget_transit_stops: Extracts stop information from GTFS data, optionally filtered by routeget_flood_warnings: Gets current flood warnings for Malaysia, filterable by state, district, and severityhello: A simple test tool to verify that the MCP server is working correctlyThe MCP server provides robust handling for data-catalogue information retrieval:
employment_sector with annual data from 2001-2022Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.