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NotHarshhaa

mainframe-mcp-server

by NotHarshhaa

scheduler_job_status

Read-onlyIdempotent

Retrieves the current status of a named mainframe batch job from configured Control-M, CA 7, or IBM Workload Automation schedulers via REST API.

Instructions

Query an external batch scheduler (Control-M, CA 7, IBM Workload Automation) for job status via its REST API. Schedulers are configured with SCHEDULER_ADAPTERS.

Input Schema

NameRequiredDescriptionDefault
jobNameYesScheduler job name, e.g. "PAYROLL_DAILY".
schedulerNoScheduler name from SCHEDULER_ADAPTERS. Required when several are configured.
environmentNoNamed target environment (see list_environments), e.g. "dev", "prod". Omit to use the server default.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.0.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so safety is covered. The description adds genuinely useful context that the call crosses a network boundary to a third-party REST API and depends on adapters being configured. It does not mention what happens when a scheduler is unreachable or unconfigured, which matters for an open-world tool.

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?

Two short sentences with no filler, and the identifying detail (external scheduler + REST) is front-loaded. The second sentence is slightly fragmentary but carries a real prerequisite, so it earns its place.

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

Completeness4/5

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

For a three-parameter, fully documented read-only lookup with annotations covering safety and openness, the description covers purpose, target systems, and configuration dependency. Return shape is not described, but no output schema exists; still, the gaps around error/timeout behavior and the sibling disambiguation keep it below 5.

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 each parameter documented in the schema itself (including the 'required when several are configured' nuance for scheduler and the list_environments pointer for environment). The description only echoes the SCHEDULER_ADAPTERS concept, adding no new syntax or format detail, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource ('Query ... job status') and adds a meaningful qualifier: it targets an external batch scheduler (Control-M, CA 7, IBM Workload Automation) over REST. That said, it does not distinguish itself from the very similar sibling get_job_status, leaving the agent to guess which one applies to a given job.

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?

It mentions the configuration prerequisite ('Schedulers are configured with SCHEDULER_ADAPTERS') but gives no when-to-use rule: nothing says to pick this over get_job_status, list_jobs, or find_failed_jobs, nor when an external scheduler lookup is the right escalation. The agent must infer the externality distinction from the product names alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.