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PyTorch Lightning MCP Server

PyTorch Lightning MCP Server

by prat24
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

lightning.inspect

Inspect a PyTorch Lightning model, runtime environment, or summary to diagnose issues and verify configuration.

Instructions

Inspect models or runtime environment.

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": {
      "what": "<what>"
    },
    "name": "lightning.inspect"
  }
}

Input Schema

NameRequiredDescriptionDefault
whatYesInspection target (model, environment, summary).
modelNoModel configuration (required for model inspection).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

C2.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It only says 'Inspect' without disclosing read-only nature, permissions, or error behavior. Minimal transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (one short sentence) but omits the 'summary' inspection target. It is adequate but could be more complete without losing conciseness.

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?

Lacks details about return format or behavior. With no output schema and no annotations, the description should provide more context on what inspection produces (e.g., JSON, console output).

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% and parameter descriptions are clear. The description adds no new parameter information beyond summarizing the overall purpose, which is redundant with the schema.

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

Purpose3/5

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

The description states 'Inspect models or runtime environment' but the 'what' parameter includes 'summary' as a target, making the description incomplete. It does not distinguish from sibling tools like lightning.checkpoint, which may also involve 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?

No guidance on when to use this tool versus alternatives. The description lacks explicit when/when-not statements, leaving the agent to infer usage context from sibling tool names.

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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