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phimage

mcp-computer-use

by phimage
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool there is no possibility of mistaking it for another tool. The tool internally distinguishes capture, click, type, scroll, and drag through its action parameter, so the surface is unambiguous.

    Naming Consistency4/5

    The single tool name 'computer_use' is clear and descriptive, though it does not follow a verb_noun pattern. There is no inconsistent naming across the set because only one name exists.

    Tool Count3/5

    One tool is borderline for such a broad domain, but it deliberately consolidates all computer-use actions behind a single action parameter. This keeps the count minimal, though splitting actions into separate tools could improve discoverability.

    Completeness4/5

    The tool covers the core GUI automation lifecycle: capture, click, type, scroll, drag, and verification via re-capture. Minor operations like explicit right-click or file upload are not named, but the overall workflow is practical and mostly complete.

  • Average 4.7/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 2 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

  • This repository is licensed under MIT License.

  • 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

  • Behavior5/5

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

    Annotations only include a title, so the description carries the full burden of behavioral disclosure. It explicitly reveals background-first input, focus-stealing only via escalation with separate approval, safety prohibitions (password/permission/payment UI, secrets, prompt injection), and failure-recovery steps — far beyond what structured data provides.

    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 long but appropriately dense: it front-loads the core action, then flows through input model, workflow, output handling, safety, failure, and prerequisites. Every sentence earns its place for a 23-parameter tool with no output schema.

    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?

    Despite minimal annotations, no output schema, and no siblings, the description covers the full operating loop (capture → act → verify), output artifacts (verdict, screenshot_path), safety rules, escalation, and error recovery. Nothing essential for correct invocation is missing.

    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?

    Schema coverage is 100%, so baseline is 3, but the description adds selection and sequencing logic: 'click by element index' vs pixel-coordinate escalation, 'pass capture_after=true' to save a round-trip, and 'set_value' for select/popup/sliders. This supplements the schema's per-parameter descriptions with actionable decision guidance.

    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 opening sentence names a concrete verb and resource ('Drive the desktop via cua-driver') and enumerates capabilities (screenshots, mouse, keyboard, scroll, drag) across platforms. This clearly defines the tool's scope and behavior, making it distinguishable even without sibling tools.

    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 provides an explicit workflow ('action='capture' ... then click by element index; re-capture after state-changing actions') and escalation logic ('when a result's verdict says to escalate... delivery_mode='foreground''). It also states prerequisites and failure recovery, but does not give an explicit 'when not to use' since no sibling alternatives exist — a minor gap.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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