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DataPulse

by data-pulse.my in Other

MCP serverPassing, checked 7 h ago

Read-only discovery for 440 Malaysian public datasets with freshness, licence, and provenance.

https://mcp.data-pulse.my/mcp
Tools
19
open to any client
Uptime
100%
last 30 days
Response time
701 ms
1.0 s slowest 5%
Last check
Passed
7 h ago, next any minute now

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How to connect

Add it to any MCP client that supports remote servers.

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

19 tools

  • search_datasets

    Use for discovery only: find DataPulse's 440 Malaysian public datasets by topic, source, or licence—for example, 'Malaysian public data inflation', licence and attribution, or a government dataset source. Returns ranked matches with id, title, source, licence, published status…

  • get_dataset

    Return full detail for one dataset id, including its latest health status and last-verified timestamp, content_freshness_date, and freshness_signal_source (last_modified, content_parse, or none). Use to fetch the provenance/citation metadata for a dataset found via…

  • get_data_passport

    Return one bounded, machine-readable Dataset Passport v1 for a canonical dataset ID. It reads the published Passport artifact only; it does not fetch an upstream source or create evidence. The Passport describes observed metadata and evidence availability, not semantic truth…

  • find_stale

    Return datasets whose status is aging, stale, or degraded, plus datasets missing from the latest health snapshot. Use when an agent needs to know which data has a freshness or schema-validity risk. Use it to enumerate freshness or schema-risk candidates; do not use it for…

  • find_anomalies

    Return datasets flagged by the latest published anomaly detection (anomalies), ranked by how far the observed update interval exceeds its threshold. Optionally require a minimum publish-reliability grade; includes pipeline-computed anomaly and reliability evidence so agents do…

  • find_deteriorating

    Return datasets whose published freshness trend is deteriorating, ranked by staleness slope. Optionally require a minimum historical anomaly rate; includes pipeline-computed trend and reliability evidence so agents do not recompute it. Use it for worsening freshness trends; do…

  • find_recovering

    Return datasets whose published freshness trend is recovering, with the fastest staleness reductions first. Includes pipeline-computed trend and publish-reliability evidence. Use it for improving freshness trends; do not use it for deterioration, anomalies, reliability grades…

  • find_unreliable

    Return datasets whose evaluated publish-reliability grade is at or below a threshold (the unreliable ones), with the worst grades and lowest on-time percentages first. Reliability measures timeliness of successful freshness observations, not uptime; sample days are included so…

  • find_schema_drift

    Return datasets with published structural or record-count drift evidence, ranked with structural changes first. Optionally require a minimum number of structural transitions; includes pipeline-computed evidence so agents do not infer drift from freshness alone. Use it for…

  • check_reconciliation

    Return the published cross-source reconciliation group for a dataset name or id, including per-member counts, dates, statuses, tolerances, and contextual deltas. A discrepancy requires human review and does not prove either source is wrong. Use it to compare a dataset with its…

  • get_provenance

    Use when asked 'can I cite this source?', for licence and attribution, or for citation-ready provenance. Returns source, steward, licence/attribution context, canonical URL, and compact published evidence context: probe time, transport, access dependency, freshness signal…

  • get_evidence

    Use for a deep evidence audit or to inspect a provenance and evidence receipt. Returns the complete published evidence receipt for one dataset: probe time, transport, access dependency, freshness, schema drift / record-count drift, tolerance, status, anomaly fields, and…

  • verify_dataset

    This is the preferred single-call pre-trust check for 'is this dataset current?', stale, unknown-freshness, degraded, or browser-dependent questions, and whenever an agent must verify before relying on data. Returns dataset metadata, published evidence and fail-closed signed…

  • get_freshness_summary

    Return a freshness-at-a-glance summary of the published catalogue: fresh, aging, stale, and reference counts plus the latest health check time. Use it for catalogue-level freshness context; do not use it to enumerate affected datasets—use find_stale instead. It reads the latest…

  • verify_evidence

    Use when a fresh, rate-limited live-vs-published comparison is needed for a direct-access dataset, for example after asking whether a government dataset is reachable now. Performs a rate-limited live GET and returns comparable transport receipts plus a match, mismatch…

  • trust_verdict

    Return published attestation facts, the unsigned methodology-versioned trust score, numeric components, and component_availability reasons, plus existing health/trend/drift/reconciliation evidence for one canonical dataset id, e.g. 'fuelprice'. This tool does not re-probe or…

  • verify_attestation

    Use to verify a signed published probe attestation after an evidence audit. Returns L1 signature, key, time, and chain-link checks; optional L2 replay of daily heads to a Git-tag anchor; and L3 scope, which requires verify_evidence for live transport. A valid signature proves…

  • find_by_licence

    Return all datasets with the given licence, summarised. Use to enumerate what's available under a specific licence for compliance/reuse scoping. Use it to enumerate one licence; do not use it to discover by topic or inspect a dataset's citation context—use search_datasets or…

  • usage_summary

    Aggregate anonymous tool usage for an inclusive ISO date range, e.g. 2026-08-01 to 2026-08-07. Returns `total_calls`, `by_outcome`, `by_tool`, `by_dataset`, `trust_verdict_calls` (the count of trust_verdict records regardless of outcome or result shape), and `trust_distribution`…

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