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ondata

CKAN MCP Server

by ondata

Search CKAN Organizations by Name

ckan_organization_search
Read-onlyIdempotent

Search for organizations in a CKAN data portal by name pattern. Returns matching organizations with dataset counts.

Instructions

Search for organizations by name pattern.

This tool provides a simpler interface than package_search for finding organizations. Wildcards are automatically added around the search pattern.

Args:

  • server_url (string): Base URL of CKAN server

  • pattern (string): Search pattern (e.g., "toscana", "salute")

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

Returns: List of matching organizations with dataset counts

Examples:

Typical workflow: ckan_organization_search → ckan_organization_show (get details) → ckan_package_search with fq="organization:name"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
patternYesName pattern to search for (wildcards added automatically, e.g., 'toscana', 'health')
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
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive nature. The description adds that wildcards are added automatically and specifies the return format (list with dataset counts), providing behavioral context beyond annotations.

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?

The description is well-structured with Args, Returns, and Examples sections. It is concise, front-loads the purpose, and every sentence adds 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?

Given 3 parameters, no output schema, and many sibling tools, the description is complete. It specifies output format, provides examples, and suggests a workflow, fully equipping an agent to use the tool correctly.

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?

Schema coverage is 100%, but the description adds meaning: explains pattern with wildcard behavior and examples, server_url as base URL, and response_format output options. Examples further clarify usage.

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 clearly states the tool searches for organizations by name pattern, specifies it is a simpler interface than package_search, and mentions that wildcards are added automatically. This distinguishes it from siblings like package_search.

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 explains when to use this tool (searching by name pattern, simpler than package_search) and provides a typical workflow (search, then show, then package_search). It does not explicitly state when not to use, but the context is clear.

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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