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jaguarkyng

Jungle Grid MCP Server

by jaguarkyng

submit_job

Submit a workload to Jungle Grid for execution on managed compute infrastructure, supporting inference, training, fine-tuning, and batch jobs with configurable image, command, and GPU resources.

Instructions

Submit a Jungle Grid workload for execution. This may start managed compute infrastructure and incur usage charges.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
envNo
argsNo
nameYes
imageYes
commandNo
metadataNo
templateNo
model_sizeNoOptional model size in GB used to select GPU capacity.
input_filesNoUploaded input references to mount under /workspace/inputs/<filename>.
routing_modeNo
script_filesNoUploaded script references to mount under /workspace/scripts/<filename>.
workload_typeYes
expected_artifactsNoExpected output files under /workspace/artifacts.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.20.2

TDQS

B3.3/5.0
Behavior4/5

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

The description adds meaningful side-effect context beyond the annotations: it may start managed compute infrastructure and incur usage charges. This is valuable for an agent deciding whether to proceed, especially since readOnlyHint is false and openWorldHint is true.

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?

Two short sentences with no filler. The core action is front-loaded, and the cost/infrastructure warning lands immediately after, making the most important behavioral information prominent.

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

Completeness2/5

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

For a complex 13-parameter submission tool with nested objects and no output schema details provided, the description is too thin. It omits workflow context such as how the submitted job can be tracked, whether it returns a job ID, and how it relates to upload_job_input or estimate_job.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description contains no parameter-level guidance, and schema description coverage is only 31%, so the description must compensate for undocumented parameters but does not. Required fields like name, workload_type, and image are not mentioned, nor are routing_mode, env, command, or metadata semantics.

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 ('Submit') and resource ('Jungle Grid workload for execution'), clearly conveying that this tool creates and launches a workload. This distinguishes it from siblings like list_jobs, get_job, cancel_job, and estimate_job without requiring schema inspection.

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?

The description does not say when to use this tool versus alternatives such as estimate_job or upload_job_input. It implies readiness to execute, but provides no explicit guidance about prerequisites, ordering, or when another sibling should be used instead.

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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