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CKAN MCP Server

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TypeScript
Hybrid

Show CKAN Dataset Details

ckan_package_show
Read-onlyIdempotent

Retrieve full metadata for any CKAN dataset, including resources, organization, tags, license, and temporal coverage. Specify the dataset ID or slug to get complete details for searching or exploring open data.

Instructions

Get complete metadata for a specific dataset (package).

Returns full details including resources, organization, tags, and all metadata fields.

Notes:

  • metadata_modified is a CKAN record timestamp (publish time on source portals, harvest time on aggregators), not the content date.

  • issued/modified are content dates when provided by the publisher.

  • JSON output adds metadata_harvested_at (same as metadata_modified).

Args:

  • server_url (string): Base URL of CKAN server

  • id (string): Dataset ID or name (machine-readable slug)

  • include_tracking (boolean): Include view/download statistics (default: false)

  • response_format ('markdown' | 'json'): Output format

Returns (JSON format): id, name, title, notes, organization, tags, state, license_title, metadata_created, metadata_modified, issued, modified, author, maintainer, frequency, language, publisher_name, holder_name, hvd_category, applicable_legislation, temporal_coverage (array of {start, end, start_equals_issued} from dct:temporal; empty if absent; start_equals_issued=true when start = issued and no end: on dcatapit portals an export default, not a data period), resources (id, name, format, url, size, datastore_active, created, last_modified, api_json_url), view_url, api_json_url

Examples:

Typical workflow: ckan_package_show → pick a resource with datastore_active=true → ckan_datastore_search (query its data)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesDataset ID (UUID) or machine-readable name slug (e.g., 'raccolta-differenziata-comuni')
server_urlYesBase URL of the CKAN server (e.g., https://dati.gov.it/opendata)
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown
include_trackingNoInclude tracking statistics

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.108

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true, but the description goes far beyond by explaining the meaning of metadata_modified vs issued/modified, the temporal_coverage edge case (start_equals_issued), and the addition of metadata_harvested_at in JSON output. This adds substantial behavioral context that annotations cannot convey, with no contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (purpose, notes, args, returns, examples, workflow) and front-loads the core purpose. It is relatively long (~300 words) but every section earns its place given the tool's complexity. It is not bloated or repetitive, though it could be slightly tightened without losing value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description fully documents the return structure, listing all fields and explaining edge cases like temporal_coverage and start_equals_issued. It also covers the response_format options, examples, and a typical workflow. Combined with annotations that handle safety, nothing an agent needs to call this tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema covers 100% of parameters with descriptions, so the baseline is 3. The description adds value by providing concrete examples, clarifying that 'id' can be a slug or UUID (though schema says the same), and explaining the response_format default. It also integrates parameter usage into the workflow, which goes beyond the schema's static definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Get complete metadata for a specific dataset (package)' – a clear verb, resource, and scope. It differentiates from siblings like ckan_package_search by emphasizing 'specific dataset' and listing the exact metadata fields returned, which makes its purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a 'Typical workflow' that shows when to use this tool (after identifying a dataset) and how it leads to ckan_datastore_search. It also includes examples and notes on timestamp semantics. However, it does not explicitly state when NOT to use it (e.g., when you lack an ID and should use search), though the 'specific dataset' phrasing implies that condition.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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