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Local Grounding MCP

Local Grounding MCP

by archie-ib-dev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

load_grounding_model

Loads the shared local grounding model to enable local inference for locating described UI targets in screenshots; simultaneous load requests queue until the model is ready.

Instructions

Load the one shared model; simultaneous calls queue.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "load_grounding_model"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses that simultaneous calls queue, but it does not state whether loading is idempotent, blocking, resource-intensive, or required before other grounding operations.

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 concise sentence with no wasted wording. The core action and the concurrency behavior are front-loaded.

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?

An output schema exists, so return values need not be explained. However, for a shared-model loading operation, the description omits important context such as whether the call is required before sibling tools and whether repeated calls are safe or simply queue unnecessarily.

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

Parameters4/5

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

The tool has zero parameters, so parameter semantics are not a meaningful gap. The baseline for a no-parameter tool 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: "Load the one shared model." It is clear what the tool does, but it does not differentiate this tool from the sibling tools such as grounding_health or locate_target.

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 gives no explicit when-to-use guidance, no prerequisites, and no alternatives. "Simultaneous calls queue" is a behavioral note, not usage guidance, so an agent is left to infer when this load step is required.

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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