dataset_columnsThe columns, which of them are numeric, the row count and the provenance banner of the HardFM dataset. Call this first to learn the schema.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It lists what information is returned, which conveys a read-only informational purpose, but it does not explicitly state that the call has no side effects or whether it is always safe.
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 a single, tight sentence that front-loads the returned data and ends with actionable guidance. Every word contributes meaning; there is no redundancy.
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?
For a zero-parameter, informational tool, the description is largely complete: it covers outputs and when to call it. The exact return shape or format is not described, but no output schema exists and the call has no inputs, so the missing detail is minor.
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 tool has zero parameters, and the schema coverage is 100%, so there is no parameter ambiguity. The description does not need to explain parameter meanings since none exist.
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 clearly states that the tool returns the columns, numeric flags, row count, and provenance banner of the HardFM dataset. It does not explicitly differentiate from siblings like dataset_provenance or dataset_stats, but the overall purpose is distinct and understandable.
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?
'Call this first to learn the schema' gives explicit usage timing and context. It does not name alternatives or exclusion cases, but the directive is strong enough for an agent to know when to invoke it.
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.
Each tool has a distinct role—schema, provenance, exact lookup, substring search, value comparison, stats, and top/bottom—so the surface is easy to navigate. The only minor ambiguity is between dataset_row, dataset_search, and dataset_compare, all of which retrieve rows but with different matching semantics.
All tools follow a consistent dataset_ prefix with lowercase snake_case names. The naming is predictable and immediately signals the domain, making it easy for an agent to infer the purpose of any tool.
Seven tools is a well-scoped count for a single-dataset read-only MCP server. Each tool covers a meaningful query mode without unnecessary duplication or bloat.
The toolset covers the main dataset exploration needs: schema discovery, provenance, exact and substring search, multi-value comparison, numeric summaries, and extreme rows. A few advanced workflows—such as arbitrary filtering, grouping, or custom aggregations—are not directly supported, but the provided tools cover most common questions.