Skip to main content
Glama
Sign In
ocr-mcp

ocr-mcp

by Prekzursil
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_engines

Check which OCR engines are available on your machine before selecting an engine for text recognition.

Instructions

List OCR engines and whether each is currently usable on this machine.

Returns JSON: for each engine -> {available, status}. Call this first to see which engines compare_engines will actually run.

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": "list_engines"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description discloses the tool's behavior well: it returns availability and status for each engine, and checks usability on the current machine. It does not cover error handling, but for a simple list tool this is sufficient.

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 sentences, no wasted words. The first sentence states the core purpose, the second adds output format and usage guidance. Highly efficient and front-loaded.

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

Completeness5/5

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

Given zero parameters and sibling tools, the description is complete. It explains the output structure and the tool's role in a workflow (called before compare_engines), which is sufficient.

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?

There are no parameters, and schema coverage is 100%. The description adds meaning by explaining what the tool does and its output, which meets the baseline for zero-parameter tools.

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 clearly states the tool lists OCR engines and their usability. It uses a specific verb ('List'), a resource ('OCR engines'), and distinguishes itself from siblings by mentioning compare_engines.

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

Usage Guidelines4/5

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

The description explicitly says 'Call this first to see which engines compare_engines will actually run,' providing clear context for when to use. It lacks explicit when-not or alternatives, but the guidance is strong.

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

Deploy Server

Other Tools