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Mrshahidali420

Pixel Bridge MCP

by Mrshahidali420
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TypeScript

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have distinct purposes: one for authentication and one for checking job status. No overlap in functionality, making them easily distinguishable.

    Naming Consistency2/5

    Tool names follow different patterns: 'get_generation_status' uses verb_noun, while 'provider_login' uses noun_verb. This inconsistency is confusing despite having only two tools.

    Tool Count2/5

    With only two tools, the server feels under-scoped for image generation. The typical range for a well-scoped server is 3-15 tools, and this falls short.

    Completeness1/5

    The server lacks essential tools like generate_image or edit_image, which are critical for its domain. The presence of only login and status checking leaves major gaps.

  • Average 4.2/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • No commit activity data available
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • 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

  • Behavior3/5

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

    No annotations exist, so the description carries full burden. It discloses blocking behavior (wait_seconds) and return content (status, paths, errors, logs), but does not explicitly state that the tool is read-only and non-destructive. This is adequate but could be more explicit.

    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?

    Single sentence, no fluff, directly conveys all necessary information. Perfectly concise.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the simple input schema (2 params, 100% coverage) and no output schema, the description covers return values and usage context well. It could mention that wait_seconds defaults to 0 (return current state), but this is already in the 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 baseline is 3. The description adds context by linking job_id to generation tools and explaining wait_seconds blocking, but this is already inferred from the schema. Minor added value.

    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 the tool checks a generation/edit job's status, returns status, saved file paths, error details, and logs. It specifies the tools that start these jobs (generate_image, edit_image, generate_with_both), making the purpose distinct from the only sibling (provider_login).

    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 implies when to use the tool (after calling generation tools) and provides clear context. It does not explicitly state when not to use it or mention alternatives, but the sibling list is minimal and unrelated, so exclusions are not critical.

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

  • Behavior5/5

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

    No annotations provided, so the description fully covers behavior: opens headed browser, waits for manual login, does not automate CAPTCHA/MFA, returns on login or timeout. Also mentions server configuration requirement.

    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, front-loading the main action. Every sentence provides necessary information without waste.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    The description explains the process and return behavior (detection or timeout) but does not specify the exact return value (e.g., success/failure). Still fairly complete for a login tool without 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% so baseline is 3. The description adds no additional meaning beyond the schema's parameter descriptions for 'provider' and 'wait_seconds'.

    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 the tool opens a provider's website in a headed browser and waits for manual login, including handling CAPTCHA/MFA. It distinctly differs from its sibling get_generation_status.

    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 explains when to use (manual login with CAPTCHA/MFA) and includes a configuration requirement for headless mode. It lacks explicit exclusion of alternatives, but the sibling tool is unrelated.

    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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