Skip to main content
Glama
lazyants

transkribus-mcp-server

by lazyants

Submit Image for Processing

transkribus_processing_submit_image

Submit a single image to Transkribus for text recognition. Provide either an image URL or base64 data (JPEG, TIFF, PNG, up to 20 MB) and receive a process ID.

Instructions

Submit a single image to the Transkribus Processing API for text recognition and get back a process ID. Supply exactly one of imageUrl or base64 (JPEG, TIFF or PNG, up to 20 MB).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYesThe image to process: exactly one of imageUrl or base64
configYesHow the image should be processed
contentNoExisting regions and lines. When supplied, line detection is skipped.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv4.0.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare the safety profile (readOnlyHint=false, idempotentHint=false, destructiveHint=false). The description adds the image format and size constraints, and notes that a process ID is returned. However, it omits important behavioral context such as whether the operation is asynchronous, authentication requirements, or failure modes.

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, front-loaded with the core action, and zero wasted words. Efficient and clear.

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?

The description covers the image parameter and return value, but it completely omits the required 'config' parameter, which has complex nested settings. It also does not explain the asynchronous nature of the operation or how the process ID should be used subsequently. Given the tool's complexity, these are notable gaps.

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%, so the schema already documents all parameters including the 'exactly one' constraint and image format details. The description repeats this constraint but adds no new parameter-level semantics beyond what is in the schema.

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 states a specific verb ('Submit'), resource ('a single image'), and purpose ('for text recognition and get back a process ID'). It clearly distinguishes itself from sibling tools by scope ('single image') and outcome ('process ID').

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 is provided on when to use this tool versus alternatives, nor are there any preconditions or exclusions. The only usage-related information is a parameter constraint ('exactly one of imageUrl or base64'), which is not usage guidance.

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