Skip to main content
Glama
ondata

CKAN MCP Server

by ondata

Show CKAN Dataset Details

ckan_package_show
Read-onlyIdempotent

Retrieve full metadata for a CKAN dataset by ID or name, including resources, organization, tags, and license information.

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, 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
Behavior4/5

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

Beyond annotations (read-only, idempotent, non-destructive), description clarifies timestamp semantics (metadata_modified vs content dates) and notes on JSON output. 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.

Conciseness5/5

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

Well-structured with sections for notes, args, returns, example, workflow. Front-loaded purpose, no filler. Every sentence informative.

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?

Despite no output schema, description provides a comprehensive list of returned fields and their meanings (e.g., metadata_modified clarified), plus workflow context. Complete for tool's purpose.

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

Parameters3/5

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

Schema already provides 100% coverage with good descriptions. Description adds usage examples and clarifies output format roles, but adds only marginal value beyond schema.

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?

Clear verb+resource ('Get complete metadata for a specific dataset'). Distinguishes from siblings like ckan_package_search and ckan_datastore_search via typical workflow note.

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?

Provides explicit typical workflow linking to subsequent tool, helping select tool in sequence. Implicitly distinguishes from search/query tools, but no explicit 'do not use when' conditions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ondata/ckan-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server