boston_datasetsSearch the City of Boston open-data catalogue (data.boston.gov, CKAN) by keyword. Returns each matching dataset's title and its queryable datastore resource ids (use with boston_query).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max datasets (1-50, default 15). | |
| query | No | Keyword(s), e.g. "parking", "trees", "budget". |
Changes observed during successful MCP inspections.
Input schema / examplesAdded value: +[
+ {
+ "query": "parking"
+ },
+ {
+ "limit": 25,
+ "query": "trees budget"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover safety (readOnly, idempotent, not destructive). Description adds that it returns dataset titles and resource ids, and links to boston_query, 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the purpose and provide essential details without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Returns no output schema, but description explains return format (title and resource ids) and relationship to boston_query. Could mention pagination or resource id format, but adequately complete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already provides 100% coverage with descriptions for both parameters. Description reiterates them and adds context (e.g., 'use with boston_query'), but does not add significant new semantic detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it searches the City of Boston open-data catalogue by keyword, returns dataset titles and resource ids, and distinguishes from sibling tools like boston_query and boston_recent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (keyword search) and mentions boston_query for querying datastores, but lacks explicit when-not-to-use or alternative conditions.
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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