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Mainframe MCP Server

Mainframe MCP Server

by rohittrimale
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

get_dataset_list

Read-only

List datasets that match a specific pattern or filter on IBM z/OS mainframes.

Instructions

List datasets matching a pattern/filter.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "dataset_pattern": "<dataset_pattern>"
    },
    "name": "get_dataset_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataset_patternYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description's 'List' is consistent but adds no new behavioral traits. It does not disclose pagination, limits, pattern syntax, or open-world implications beyond the annotation.

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 a single sentence with no redundant words. It is front-loaded with the action and immediately states the purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple input (one parameter), annotations covering read-only and non-destructive behavior, and an existing output schema, the description is adequate but lacks details about result limits, paging, or pattern behavior. More context would improve agent decision-making.

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?

The schema has 0% description coverage, so the description must compensate. It adds context that 'dataset_pattern' is a pattern/filter, which gives some semantic meaning beyond the type string. However, it does not specify syntax (e.g., wildcards, regex) or required format.

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 uses a specific verb ('List') and resource ('datasets') and includes 'matching a pattern/filter', clearly distinguishing it from sibling tools that target specific dataset types (e.g., get_cobol, get_copybook) or other actions (scan, delete).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. There are many sibling tools (e.g., search_seq_datasets, scan_source) with overlapping purposes, but the description offers no distinction or exclusion criteria.

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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