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CKAN MCP Server

by ondata

Analyze CKAN Datasets and DataStore Schema

ckan_analyze_datasets
Read-onlyIdempotent

Analyze CKAN datasets to list resources and inspect DataStore field schemas, including names, types, labels, and record counts, enabling informed data queries.

Instructions

Search datasets and inspect the DataStore schema of queryable resources.

For each dataset found, lists all resources. For DataStore-enabled resources, fetches the full field schema (name, type, and label/notes when available) plus total record count — all in one call.

Use this before ckan_datastore_search to understand what fields are available and what data to expect.

Args:

  • server_url (string): Base URL of CKAN server

  • q (string): Solr search query (e.g. "incidenti", "title:ambiente")

  • rows (number): Max datasets to analyze (default 5, max 20)

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

Returns: For each dataset: title, ID, organization, and per DataStore resource: field schema with label/notes (when available from DataStore Dictionary) and record count.

Typical workflow: ckan_analyze_datasets → ckan_datastore_search (with known field names)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSolr search query (e.g. 'incidenti', 'title:ambiente')
rowsNoMax datasets to analyze (default 5, max 20)
server_urlYesBase URL of the CKAN server (e.g., https://dati.comune.messina.it)
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 indicate read-only, idempotent, non-destructive behavior. The description adds transparency by detailing that it lists all resources for each dataset and fetches field schema and record count for DataStore-enabled resources, going beyond annotation basics.

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 an overview, detail, usage guidance, and parameter list. It is concise but informative, with no unnecessary words.

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 lacking an output schema, the description thoroughly explains the return structure (dataset details and per-resource info). The typical workflow guidance adds completeness, making it easy for an agent to understand the tool's role.

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 coverage is 100% with all parameters described. The description's Args section largely repeats schema information without adding new semantic meaning, so baseline score of 3 is appropriate.

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's purpose: searching datasets and inspecting DataStore schema. It distinguishes from sibling tools like ckan_datastore_search by specifying that this tool is used to understand available fields before performing a 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 explicitly advises using this tool before ckan_datastore_search, providing a typical workflow. While it does not list when not to use it, the context is clear and helpful.

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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