datasetsSearch dataset catalogue.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | ||
| offset | No |
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Total number of results matching query | |
| results | No | Array of dataset results |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "limit": 10,
+ "query": "crime"
+ },
+ {
+ "limit": 20,
+ "offset": 0,
+ "query": "311 complaints"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Socrata catalog search results",
+ "properties": {
+ "count": {
+ "description": "Total number of results matching query",
+ "type": "number"
+ },
+ "results": {
+ "description": "Array of dataset results",
+ "items": {
+ "properties": {
+ "classification": {
+ "description": "Dataset classification information",
+ "type": "object"
+ },
+ "resource": {
+ "description": "Dataset resource metadata",
+ "type": "object"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare the tool as read-only, open-world, idempotent, and non-destructive. The description adds no additional behavioral context beyond 'search', such as pagination behavior, result format, or any side effects. It neither contradicts the annotations nor enriches the safety profile.
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?
The description is one short sentence that directly states the purpose without any extraneous words. It is appropriately concise and front-loaded, earning full marks for efficiency.
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?
While the tool has an output schema (reducing the need to explain return values), the description fails to clarify how the three parameters should be used, what constitutes a valid query, or what the catalogue contains. Given the zero schema description coverage, the description is not complete enough for an agent to confidently invoke the tool correctly.
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?
The input schema has zero description coverage for its three parameters (limit, query, offset), and the tool description provides no explanation of their meaning or usage. The examples in the schema offer minimal hint, but the description itself adds no parameter semantics, leaving the agent without sufficient guidance on how to construct a valid request.
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?
The description 'Search dataset catalogue' uses a specific verb ('Search') and resource ('dataset catalogue'), which clearly states the tool's function. It distinguishes itself from sibling tools by explicitly mentioning the catalogue, making the purpose unambiguous.
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?
There is no guidance on when to use this tool versus alternatives. The description only states what it does, not when it should be preferred or avoided. No exclusions or alternative tool references are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes, but ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim have overlapping functionality in answering factual questions. The detailed descriptions help differentiate them, though some confusion may still arise.
All tool names follow a consistent snake_case convention with a verb_noun pattern (e.g., compare_entities, resolve_entity). No mixing of camelCase or other styles, making the naming predictable and uniform.
34 tools is on the higher side, but many are meta-tools (discover, feedback, subscriptions) and some are redundant (ask_pipeworx vs grounded). While the scope is broad, the count could be trimmed for tighter focus.
The server covers a wide range of domains (SEC, FDA, FRED, prediction markets, etc.) with strong read and analysis capabilities. Missing update/delete operations and direct trading, but comprehensive for data retrieval and analysis.