Skip to main content
Glama

SiteCheck

by io.github.bck-stack
OverviewDiscussionsAdmin

Ocr

ocr
Read-only

Reads the text of an image (JPEG, PNG, GIF or WEBP, up to 4 MB) with Llama 3.2 11B Vision on Workers AI. Send an https url or base64 image, and optionally a language hint. Returns the full text with its line breaks, the lines, a language guess and the model that answered. An image with no readable text is a 422 and is not charged. Price: $0.003 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

NameRequiredDescriptionDefault
urlNohttps URL of the image
imageNoAlternative: the image as base64, up to 4 MB
languageNoOptional hint, e.g. English or German

Output Schema

NameRequiredDescriptionDefault
mimeNo
textNo
bytesNo
linesNo
modelNo
languageNo
checkedAtNo
languageNameNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "bytes": {},
+    "checkedAt": {},
+    "language": {},
+    "languageName": {},
+    "lines": {},
+    "mime": {},
+    "model": {},
+    "text": {}
+  },
+  "type": "object"
+}
  2. Added

TDQS

A4.3/5.0
Behavior5/5

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

The description adds substantial behavioral detail beyond the annotations: pricing in USDC, x402 payment chains, no charge for failed calls, a 422 for images with no readable text, and the exact model used. These details are highly useful for an agent planning a call.

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 dense but front-loaded: core purpose first, then invocation, return information, error behavior, and pricing. Every sentence provides actionable information without padding.

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 the tool's complexity, the description is complete. It covers inputs, formats, limits, return fields, error behavior, pricing, and model, while safety is already covered by annotations and return structure is backed by an output schema.

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 description coverage is 100%, so the schema already documents url, image, and language. The description reinforces that url and image are alternatives and that language is an optional hint, but adds little syntax or meaning beyond 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 and resource: reads the text of an image via OCR. It names supported formats, size limit, and the underlying vision model, so an agent can distinguish this from general image or description tools.

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

Usage Guidelines3/5

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

It explains how to invoke the tool by sending an HTTPS URL or base64 image, and notes an optional language hint. However, it does not explicitly state when to use this tool instead of siblings such as describe_image or extract, nor does it list exclusions.

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

All SiteCheck toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources