MCP 服务器

datapulse-my

Trust layer for 375 Malaysian public datasets. Independent probes every 15 min, 10-status taxonomy, machine-readable licence metadata, read-only MCP. No API key.

README

DataPulse MY

Live dashboard: https://www.data-pulse.my

Open in Google Colab:

🤖 AI-agent-ready — Wire DataPulse MY into Claude Desktop, Cursor, Cline, or any MCP-compatible client with one config block. Your agent gets 375 official Malaysian datasets — including 30 GTFS transit feeds (KTMB, Prasarana, BAS.MY) — with declared licences and an honest nine-status trust taxonomy instead of a blanket green checkmark.

→ Connect your AI agent in 30 seconds

DataPulse MY is an open-source trust layer for Malaysian public data. It makes official datasets easier to assess and reuse by publishing a small manifest, human-readable health reports, and machine-readable health envelopes.

It does not replace the official source. It documents what is available, whether it is fresh, how its schema behaves, and which collection quirks users need to handle.

Who it is for

Journalists and researchers checking whether a public dataset is usable.
Civic technologists building reproducible data pipelines.
Public servants improving the discoverability and reliability of open data.
Developers who need stable, machine-readable dataset health metadata.

Use this for

Journalist fact-check: before citing a fuel price figure, check fuelprice freshness to make sure it's current.
Pipeline health gate: fail the build when a required dataset probe has remained unavailable for more than 24 hours.
RAG knowledge base: consume the JSON envelopes as structured context for a chatbot answering "what's the latest BNM rate?"

Dataset health

Health is reported as fresh, aging, stale, discontinued, degraded, browser-dependent, unreachable, unknown, unknown-freshness, or reference. Unknown freshness means the URL and content shape work, but neither a Last-Modified header nor a parseable content date proves when the data was updated. Reference means versioned lookup data is reachable and its record count is measured, while date-based freshness does not apply. The public _trust_summary shows the distribution and explicitly counts missing freshness and row-count signals.

Discontinued — The source has stopped publishing new data. The data is frozen at the last known content date. This is not a freshness failure — it's a publisher decision.

Current distribution (_trust_summary): 95 fresh · 108 aging · 153 stale · 1 discontinued · 5 browser-dependent · 13 reference

Subscribe: RSS feed — get notified when dataset health changes.

⚠️ Status: active development. Dashboards and health snapshots update as probes complete. Per-dataset reports under data/{id}.md may briefly lag behind the live health snapshot in health/latest.json (a regeneration gap that is being closed). Coverage and quality improve with each tagged release; expect rough edges. Track progress via the GitHub Releases page — v0.4.0 is the current milestone.

Browser-dependent datasets

Five sources (currently 1.4% of the catalogue) require a real browser to probe because their source pages render client-side JavaScript: eperolehan-diklankan, doe_apims, doe_rqims, doe_mqims, and kkm_idengue.

DataPulse uses Camofox, a self-hosted patched headless-Chromium sidecar, to probe these. The probe path is check.sh → Camofox sidecar → DOM snapshot → content-date extraction.

To enable browser probing:

Run the Camofox Docker sidecar on a reachable address (default http://localhost:9377). The probe script and the GitHub Actions workflow pick this up from the CAMOFOX_BASE_URL environment variable; nothing in this repo encodes a public IP.
Set CAMOFOX_BASE_URL to that address.
Restart the timer with systemctl restart datapulse-health.timer.

Without Camofox, those five datasets will sit at browser-dependent — the honest status: DataPulse cannot probe them without a browser, so it says so rather than failing silently. See scripts/smoke_browser_probes.sh for isolated smoke tests.

Legal

DataPulse probes publicly-published open-data sources. We do not bypass authentication, CAPTCHAs, or terms-of-service restrictions. Every source we probe is publicly available without login; the data is aggregate/non-personal; and the probe respects each dataset's declared refresh frequency.

All scraping is rate-limited (15-minute cadence, dataset-tier cadence applied) and identifies itself via User-Agent. Sources we cannot probe without authentication, CAPTCHA bypass, or ToS violation are marked unreachable or browser-dependent — never silently scraped through a workaround.

If you are a data source maintainer and would like DataPulse to adjust its probe cadence, exclude a dataset, or remove it from the manifest, please open a GitHub issue or contact the maintainers.

AI-agent-ready — what it means for you

Give your organisation's AI tools current, licensed, and verified Malaysian public data without first building a custom integration. DataPulse MY makes the full portfolio discoverable from one self-describing index, ready for agents, RAG systems, and internal knowledge tools to consume.

What being AI-ready gives you

Zero integration work: an AI agent or LLM/RAG system fetches one llms.txt and can use the entire portfolio immediately — no scraping, API-key setup, or data-format reverse-engineering.
Honest freshness signals: a 15-minute timer probes datasets when their cadence tier is due, separating HTTP reachability, browser dependency, schema validity, and source freshness so missing evidence is visible instead of being labelled healthy.
Machine-readable and licence-clear: every dataset has a JSON envelope with its schema, licence, and refresh cadence, giving legal and engineering teams the information they need to approve and integrate it.
Trustworthy for AI: verified official sources and explicit licences let agents cite and use the data without permission ambiguity.
RAG and knowledge-base ready: drop the envelopes into a retrieval pipeline to ground chatbots and AI tools in current Malaysian public data.

Every manifest dataset declares either CC BY 4.0 or OGL licensing and is assessed with the honest nine-status trust taxonomy.

MCP server (read-only)

DataPulse MY also exposes an AI-ready, read-only MCP server so agents can query the catalogue natively:

Endpoint: https://mcp.data-pulse.my/mcp (Streamable HTTP, no auth)
5 tools: search_datasets, get_dataset, find_stale, get_provenance, find_by_licence
3 resources: datapulse://index, datapulse://licences, datapulse://{dataset_id}

The public endpoint is live and serves all 5 read-only tools over the 375-dataset catalogue.

Connect from Claude Desktop:

{
  "mcpServers": {
    "datapulse-my": {
      "transport": "streamable-http",
      "url": "https://mcp.data-pulse.my/mcp"
    }
  }
}

See llms.txt for the full discovery index, and docs/mcp-deploy.md for the deployment architecture.

How to consume the data

Verify access:

curl -s https://r3dz4r.github.io/datapulse-my/llms.txt

llms.txt — curated dataset index
datapulse.json — manifest with a declared $schema
health/latest.json — latest freshness snapshot
feed.xml — dataset health change feed
datapulse.schema.json — manifest schema

To consume the portfolio:

Fetch llms.txt for the curated index.
Fetch datapulse.json for the machine-readable manifest, including licence, refresh cadence, and geographic coverage.
Fetch health/latest.json to check freshness before use.
Cite each dataset according to its licence and attribution requirements.

robots.txt allows all agents; scripts/verify_agent_ready.sh is the agent-consumer self-test.

For humans wiring their own agents: see the MCP server section below for the Claude Desktop / Cursor / Cline config block, or the full integration guide at docs/mcp-deploy.md.

Wire it into Claude Desktop via claude_desktop_config.json (30 seconds, no API key):

{
  "mcpServers": {
    "datapulse-my": {
      "transport": "streamable-http",
      "url": "https://mcp.data-pulse.my/mcp"
    }
  }
}

Restart Claude Desktop, confirm the hammer icon shows "datapulse-my" with 5 tools: search_datasets, get_dataset, find_stale, get_provenance, find_by_licence. Cursor / Cline use the same JSON in their MCP config panel.

Included datasets

Malaysian Fuel Prices — Samples: CSV, JSON
ePerolehan Tender Notices (DIIKLANKAN) — Sample JSON
PriceCatcher (Grocery Prices) — Samples: main CSV, item lookup, premise lookup

Daily reference data

Daily-published reference datasets from official Malaysian sources. Each agency publishes on its own schedule, declared in refresh_frequency; the dashboard combines the date-only source value with the publication time and does not infer a time from midnight or UTC conversion.

Bank Negara Malaysia (BNM)

MET Malaysia

MET Malaysia Weather Forecast — Samples: CSV, JSON

Department of Environment (DOE)

KKM (Ministry of Health)

KKM iDengue Weekly Dengue Cases — Sample JSON

OpenDOSM (DOSM open data portal)

data.gov.my

GTFS transit feeds

The transport namespace adds 16 GTFS Static schedule ZIPs and 14 GTFS Realtime vehicle-position protobuf feeds for KTMB, Prasarana, and BAS.MY services. Static samples are under samples/gtfs-static/ and realtime snapshots are under samples/gtfs-realtime/.

DataPulse MY currently tracks the portfolio declared in datapulse.json.

Current coverage

Refresh cadence

Dataset	Refresh cadence
Malaysian Fuel Prices (`fuelprice`)	Weekly
ePerolehan Tender Notices (`eperolehan-diklankan`)	Hourly
PriceCatcher (`pricecatcher`)	Monthly
BNM Daily Exchange Rates (`exchangerates_daily_0900`)	Daily on weekdays at 0900 MYT
BNM Daily Exchange Rates (`exchangerates_daily_1130`)	Daily on weekdays at 1130 MYT
BNM Daily Exchange Rates (`exchangerates_daily_1200`)	Daily on weekdays at 1200 MYT
BNM Daily Exchange Rates (`exchangerates_daily_1700`)	Daily on weekdays at 1700 MYT
MET Malaysia Weather Forecast (`met_weather`)	Daily
DOE APIMS Air Quality (`doe_apims`)	Hourly
DOE RQIMS River Water Quality (`doe_rqims`)	Hourly
DOE MQIMS Marine Water Quality (`doe_mqims`)	Monthly
KKM iDengue (`kkm_idengue`)	Daily
OpenDOSM Crime by District (`dosm_crime_district`)	Annual
OpenDOSM CPI by State (`dosm_cpi_state`)	Monthly
OpenDOSM GDP by State (`dosm_gdp_state_real_supply`)	Annual
OpenDOSM Quarterly Real GDP (`dosm_gdp_qtr_real`)	Quarterly
OpenDOSM Annual Real GDP by Supply Sector (`dosm_gdp_annual_real_supply`)	Annual
OpenDOSM Trade Headline (`dosm_trade_headline`)	Monthly
OpenDOSM CPI Inflation by Division (`dosm_cpi_inflation`)	Monthly
OpenDOSM Trade by End Use (`dosm_trade_enduse_bec`)	Monthly
OpenDOSM Labour Force Statistics (`dosm_lfs_qtr`)	Quarterly
OpenDOSM Labour Force Statistics by State (`dosm_lfs_qtr_state`)	Quarterly
OpenDOSM Employment by Sector and Sex (`dosm_employment_sector`)	Annual
OpenDOSM Population by State (`dosm_population_state`)	Annual
OpenDOSM Nominal GDP by Supply Sector (`dosm_gdp_annual_nominal_supply`)	Annual
OpenDOSM Quarterly Nominal GDP (`dosm_gdp_qtr_nominal`)	Quarterly
OpenDOSM Seasonally Adjusted Real GDP (`dosm_gdp_qtr_real_sa`)	Quarterly
OpenDOSM Annual Nominal GDP and GNI (`dosm_gdp_gni_annual_nominal`)	Annual
OpenDOSM Core CPI Inflation (`dosm_cpi_core_inflation`)	Monthly
OpenDOSM State CPI Inflation (`dosm_cpi_state_inflation`)	Monthly
OpenDOSM Producer Price Index (`dosm_ppi`)	Monthly
OpenDOSM Annual Labour Force Statistics (`dosm_lfs_year`)	Annual
OpenDOSM Monthly Labour Force Statistics (`dosm_lfs_month`)	Monthly
OpenDOSM Trade by SITC Section (`dosm_trade_sitc_1d`)	Monthly
OpenDOSM Export-Oriented IPI (`dosm_ipi_export`)	Monthly
OpenDOSM Domestic-Oriented IPI (`dosm_ipi_domestic`)	Monthly
data.gov.my Interest Rates (`dgm_interest_rates`)	Monthly
data.gov.my Federal Revenue (`dgm_federal_finance_qtr_revenue`)	Quarterly
data.gov.my Federal Operating Expenditure (`dgm_federal_finance_qtr_oe`)	Quarterly
data.gov.my State Government Expenditure (`dgm_state_finance_expenditure`)	Annual
data.gov.my Money Aggregates (`dgm_money_aggregates`)	Monthly
data.gov.my Currency in Circulation (`dgm_currency_in_circulation`)	Monthly
data.gov.my Payment Systems (`dgm_payments_systems`)	Monthly
data.gov.my Payment Instruments (`dgm_payments_instruments`)	Monthly
data.gov.my Payment Channels (`dgm_payments_channels`)	Monthly
data.gov.my Annual Interest Rates (`dgm_interest_rates_annual`)	Annual
data.gov.my EPF Dividend Rates (`dgm_epf_dividend`)	Annual
data.gov.my Vehicle Registrations by Type and Fuel (`dgm_vehicle_registrations_type_fuel`)	Monthly
data.gov.my FPX Transactions (`dgm_payments_transactions_fpx`)	Daily
OpenDOSM Births by State (`dosm_birth_state`)	Annual
OpenDOSM Deaths by State (`dosm_death_state`)	Annual
OpenDOSM Maternal Deaths by State (`dosm_death_maternal_state`)	Annual
OpenDOSM Marriages by State and Sex (`dosm_marriages_state`)	Annual
data.gov.my Hospital Beds (`dgm_hospital_beds`)	Annual
data.gov.my Healthcare Staff (`dgm_healthcare_staff`)	Annual
data.gov.my Blood Donations by State (`dgm_blood_donations_state`)	Daily
data.gov.my Infant Immunisation (`dgm_infant_immunisation`)	Annual
data.gov.my Sexually Transmitted Diseases by State (`dgm_std_state`)	Annual
data.gov.my PeKaB40 Screenings by State (`dgm_pekab40_screenings_state`)	Daily
data.gov.my Malaysian National Health Accounts (`dgm_mnha`)	Annual
data.gov.my Electricity Consumption (`dgm_electricity_consumption`)	Monthly
data.gov.my Electricity Supply (`dgm_electricity_supply`)	Monthly
data.gov.my Water Consumption (`dgm_water_consumption`)	Annual
data.gov.my Water Production (`dgm_water_production`)	Annual
data.gov.my Treated Water Access (`dgm_water_access`)	Annual
data.gov.my Public Transport Ridership (`dgm_ridership_headline`)	Daily
data.gov.my KTMB Ridership (`dgm_ktmb_ridership_monthly`)	Monthly
data.gov.my Cellular Subscribers (`dgm_cellular_subscribers`)	Annual
data.gov.my Prisoners by State and Sex (`dgm_prisoners_state`)	Annual
data.gov.my Drug Addicts by State and Age (`dgm_drug_addicts_age`)	Annual
data.gov.my Female Representation in Local Authorities (`dgm_local_authority_sex`)	Annual
data.gov.my Female Representation in Parliament (`dgm_parliament_sex`)	Annual
data.gov.my Marine Fish Landings (`dgm_fish_landings`)	Monthly
data.gov.my Crops by State (`dgm_crops_state`)	Annual
data.gov.my Schools by District (`dgm_schools_district`)	Annual
OpenDOSM Household Income, Malaysia (`dosm_hh_income`)	Biennial to triennial (survey years)
OpenDOSM Household Income by State (`dosm_hh_income_state`)	Biennial to triennial (survey years)
OpenDOSM Household Income by District (`dosm_hh_income_district`)	Biennial to triennial (survey years)
OpenDOSM Poverty, Malaysia (`dosm_hh_poverty`)	Biennial to triennial (survey years)
OpenDOSM Poverty by State (`dosm_hh_poverty_state`)	Biennial to triennial (survey years)
OpenDOSM Poverty by District (`dosm_hh_poverty_district`)	Biennial to triennial (survey years)
OpenDOSM Income Inequality, Malaysia (`dosm_hh_inequality`)	Biennial to triennial (survey years)
OpenDOSM Income Inequality by State (`dosm_hh_inequality_state`)	Biennial to triennial (survey years)
OpenDOSM Income Inequality by District (`dosm_hh_inequality_district`)	Biennial to triennial (survey years)
OpenDOSM Household Expenditure by DUN (`dosm_hh_expenditure_dun`)	Biennial to triennial (survey years)
OpenDOSM Household Expenditure by Parliament (`dosm_hh_expenditure_parlimen`)	Biennial to triennial (survey years)
OpenDOSM Population, Malaysia (`dosm_population_malaysia`)	Annual
OpenDOSM Population by Parliament (`dosm_population_parlimen`)	Annual
OpenDOSM Deaths by District and Sex (`dosm_death_district_sex`)	Annual
OpenDOSM Marriages by State, Age, and Sex (`dosm_marriages_state_age`)	Annual
OpenDOSM Fertility (`dosm_fertility`)	Annual
OpenDOSM Maternal Deaths, Malaysia (`dosm_death_maternal`)	Annual

How to use it

Start with datapulse.json to discover datasets and their official sources. Follow each health_report link for a plain-language assessment, or consume the matching file under data/json/ in an automated workflow.

For example, a data pipeline can inspect status, content_freshness_date, and freshness_signal_source before processing a source, while a researcher can review the known quirks before designing a collection method.

Monitoring

The VPS datapulse-health.timer wakes every 15 minutes and runs only the datasets whose cadence tier is due.
GitHub Actions performs a full weekly probe as a fallback and republishes the generated health, badge, feed, README, and changelog artifacts.
RSS feed — available.
Status badges — available.
More datasets — planned.

Adopt a dataset

Know a Malaysian public dataset that deserves dependable health metadata? Adopt it: verify its source and licence, document its schema and quirks, and submit a health report. See CONTRIBUTING.md for the expected three-file contribution model.

New contributors can start with the repository's Good first issues or propose a dataset through the GitHub issue forms. Maintainers use good first issue (yellow), adopt-a-dataset (blue), freshness-check (blue), bug (red), documentation (blue), question (purple), and wontfix (gray) to route contributions.

Licence

DataPulse MY is released under the MIT License. Source datasets remain subject to the licences and attribution requirements stated in their individual health reports.