visionMCP

extract_text

Extracts readable text from images using OCR, enabling retrieval of text from photos, scans, and screenshots for digital use.

Instructions

Read all text in an image (OCR).

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": {
      "image": "<image>"
    },
    "name": "extract_text"
  }
}

Input Schema

Name	Required	Description	Default
`image`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 19, 2026

TDQS

B3.1/5.0

Behavior2/5

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

No annotations are provided, so the description alone must disclose behavior. It only states the core action without addressing input format (URL, base64, path), output structure, error handling, or whether the operation is strictly read-only. This is insufficient for an agent to fully anticipate behavior.

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 that efficiently conveys the tool's purpose. No wasted words or redundant information.

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?

Although the tool has an output schema (not shown) and only one parameter, the description is incomplete: it does not specify how the image should be provided, what the output precisely is (e.g., raw text, JSON list), or any limitations. The lack of parameter clarification makes the tool under-specified for reliable invocation.

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

Parameters1/5

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

The schema has one parameter 'image' of type string with no description and 0% schema description coverage. The description fails to explain what the image parameter expects (e.g., URL, base64, local path) or any constraints. This leaves the parameter meaning completely ambiguous.

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 'Read all text in an image (OCR)' with a specific verb (read) and resource (image), and the OCR clarification distinguishes it from siblings like describe_image or ask_about_image. It is unambiguous and sets the tool apart.

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?

The description implies usage for OCR extraction but provides no explicit guidance on when to choose it over alternatives such as describe_image or ask_about_image. No exclusions or comparison are mentioned, so it only implicitly differentiates.

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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