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Ismapik

browser-ocr-mcp

by Ismapik
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Local

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    Both tools perform OCR but on clearly distinct inputs: one captures the current browser page via screenshot, the other processes an image file or URL. No ambiguity in their purposes.

    Naming Consistency5/5

    Both tools use a consistent snake_case naming pattern with a source prefix (browser_, ocr_) followed by the action (ocr, image). The pattern is straightforward and predictable.

    Tool Count4/5

    With only 2 tools, the server is lean but covers the core OCR use cases. While slightly below the typical 3-15 range, it feels appropriately scoped for a focused OCR utility.

    Completeness4/5

    The two tools cover the primary OCR scenarios: extracting text from the live browser page and from external images. Minor gaps like language configuration or PDF support exist but are not essential for basic usage.

  • Average 3.6/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 3 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

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  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior3/5

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

    With no annotations, the description must disclose behavioral traits. It explains the screenshot and OCR process, and notes the dependency on Chromium. However, it does not specify return format, performance considerations, or error conditions. This is adequate but could be more thorough.

    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 two sentences, highly concise. The first sentence states the action and method, the second states a prerequisite. No wasted words; each sentence serves a purpose.

    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?

    Given the complexity (screenshot + OCR) and absence of output schema, the description should explain what is returned. It says 'extract all visible text' but not how that text is provided (e.g., as a string, file, or list). It also lacks error cases or performance notes. This is incomplete for a tool with no 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 coverage is 100% for the single parameter 'fullPage', so the baseline is 3. The description adds no additional meaning beyond what the schema already provides ('Capture the full scrollable page instead of just the viewport. Default: false.').

    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 clearly states the tool takes a screenshot and extracts text using OCR. However, it does not explicitly differentiate from the sibling tool 'ocr_image', which likely operates on an existing image. The verb 'take' and resource 'browser page' are specific, but sibling distinction is implicit.

    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 mentions a prerequisite (Chromium with debugging port) but provides no guidance on when to use this tool versus alternatives like 'ocr_image'. Usage context is implied (when needing text from a browser page) but lacks explicit when-to-use or when-not-to-use instructions.

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

  • Behavior3/5

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

    With no annotations, the description carries full responsibility. It discloses local processing and privacy, but omits important behavioral details such as output format, supported image formats beyond mention, error handling, and synchronous vs asynchronous execution.

    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 concise with three sentences, front-loading the main purpose. No extraneous information; every sentence adds value.

    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?

    While the description covers input types and key traits (local, private), it lacks information about the output (e.g., no mention of return value or structure). Given no output schema, this gap reduces completeness.

    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?

    Both parameters have schema descriptions, and the tool description adds value by providing usage context (e.g., 'Use this after taking a screenshot...') for the 'path' parameter, going beyond the schema.

    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 clearly states the tool extracts text from an image using local Tesseract.js OCR, specifying both input types (file path or URL). However, it does not explicitly differentiate from the sibling tool 'browser_ocr'.

    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 provides a specific usage hint ('Use this after taking a screenshot...') but lacks explicit guidance on when not to use, prerequisites, or alternatives beyond one example.

    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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  • Evaluate tool definition quality.

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